Triple
T12269415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CHIPS and Science Act of 2022 |
E292432
|
entity |
| Predicate | acronymMeaning |
P43
|
FINISHED |
| Object |
Creating Helpful Incentives to Produce Semiconductors
Creating Helpful Incentives to Produce Semiconductors is the full name behind the CHIPS and Science Act of 2022, a major U.S. law aimed at boosting domestic semiconductor manufacturing and technological competitiveness.
|
E974227
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Creating Helpful Incentives to Produce Semiconductors | Statement: [CHIPS and Science Act of 2022, acronymMeaning, Creating Helpful Incentives to Produce Semiconductors]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Creating Helpful Incentives to Produce Semiconductors Context triple: [CHIPS and Science Act of 2022, acronymMeaning, Creating Helpful Incentives to Produce Semiconductors]
-
A.
“Cramming more components onto integrated circuits”
“Cramming more components onto integrated circuits” is the landmark 1965 article by Gordon E. Moore that introduced the observation later known as Moore’s Law, predicting the exponential growth of transistor density on integrated circuits.
-
B.
Mead–Conway VLSI design revolution
The Mead–Conway VLSI design revolution was a transformative shift in microchip design methodology that introduced simplified, scalable design rules and modular, high-level approaches, enabling widespread, university-level integrated circuit design and catalyzing the modern semiconductor industry.
-
C.
International Technology Roadmap for Semiconductors
The International Technology Roadmap for Semiconductors was a collaborative industry effort that forecasted and coordinated global semiconductor technology development, guiding research and manufacturing priorities for chip scaling and performance.
-
D.
Semiconductor Systems
Semiconductor Systems is a major business division of Applied Materials that develops and supplies equipment and technologies used in the manufacturing of semiconductor chips.
-
E.
“Design of ion-implanted MOSFET’s with very small physical dimensions”
“Design of ion-implanted MOSFET’s with very small physical dimensions” is the seminal 1974 paper by Robert H. Dennard and colleagues that introduced the scaling theory for MOSFETs, forming the basis of Dennard scaling and decades of CMOS miniaturization.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Creating Helpful Incentives to Produce Semiconductors Triple: [CHIPS and Science Act of 2022, acronymMeaning, Creating Helpful Incentives to Produce Semiconductors]
Generated description
Creating Helpful Incentives to Produce Semiconductors is the full name behind the CHIPS and Science Act of 2022, a major U.S. law aimed at boosting domestic semiconductor manufacturing and technological competitiveness.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Creating Helpful Incentives to Produce Semiconductors Target entity description: Creating Helpful Incentives to Produce Semiconductors is the full name behind the CHIPS and Science Act of 2022, a major U.S. law aimed at boosting domestic semiconductor manufacturing and technological competitiveness.
-
A.
“Cramming more components onto integrated circuits”
“Cramming more components onto integrated circuits” is the landmark 1965 article by Gordon E. Moore that introduced the observation later known as Moore’s Law, predicting the exponential growth of transistor density on integrated circuits.
-
B.
Mead–Conway VLSI design revolution
The Mead–Conway VLSI design revolution was a transformative shift in microchip design methodology that introduced simplified, scalable design rules and modular, high-level approaches, enabling widespread, university-level integrated circuit design and catalyzing the modern semiconductor industry.
-
C.
International Technology Roadmap for Semiconductors
The International Technology Roadmap for Semiconductors was a collaborative industry effort that forecasted and coordinated global semiconductor technology development, guiding research and manufacturing priorities for chip scaling and performance.
-
D.
Semiconductor Systems
Semiconductor Systems is a major business division of Applied Materials that develops and supplies equipment and technologies used in the manufacturing of semiconductor chips.
-
E.
“Design of ion-implanted MOSFET’s with very small physical dimensions”
“Design of ion-implanted MOSFET’s with very small physical dimensions” is the seminal 1974 paper by Robert H. Dennard and colleagues that introduced the scaling theory for MOSFETs, forming the basis of Dennard scaling and decades of CMOS miniaturization.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cdea6e881908e13f8259bad6ddc |
completed | April 10, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e6799088190a5644267733ca2e5 |
completed | May 2, 2026, 3:55 p.m. |
| NEDg | Description generation | batch_69f61f5bc1fc8190af9d74acc307ebe1 |
completed | May 2, 2026, 3:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6203ef5008190af9103460b096cff |
completed | May 2, 2026, 4:03 p.m. |
Created at: April 8, 2026, 9:52 p.m.