Triple
T2051215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mac OS X 10.0 Cheetah |
E45571
|
entity |
| Predicate | includesComponent |
P1393
|
FINISHED |
| Object |
Quartz
Quartz is Apple's 2D graphics rendering and compositing engine that underpins the visual display system in macOS.
|
E229050
|
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: Quartz | Statement: [Mac OS X 10.0 Cheetah, includesComponent, Quartz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quartz Context triple: [Mac OS X 10.0 Cheetah, includesComponent, Quartz]
-
A.
Quartz
Quartz is a digital news outlet known for its global business journalism, data-driven reporting, and mobile-first storytelling.
-
B.
Areia
Areia is a historic colonial-era city in the Brazilian state of Paraíba, known for its preserved architecture and cultural heritage.
-
C.
Talx
Talx is a workforce solutions and employment verification company that operates as a subsidiary of the credit reporting agency Equifax.
-
D.
Aswan granite
Aswan granite is a durable, reddish granite from the Aswan region of Egypt, historically quarried for monumental architecture such as obelisks, statues, and temple elements.
-
E.
Beryl
Beryl is a given name that can be used for people of any gender, historically more common as a female name in English-speaking countries.
- 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: Quartz Triple: [Mac OS X 10.0 Cheetah, includesComponent, Quartz]
Generated description
Quartz is Apple's 2D graphics rendering and compositing engine that underpins the visual display system in macOS.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Quartz Target entity description: Quartz is Apple's 2D graphics rendering and compositing engine that underpins the visual display system in macOS.
-
A.
Quartz
Quartz is a digital news outlet known for its global business journalism, data-driven reporting, and mobile-first storytelling.
-
B.
Areia
Areia is a historic colonial-era city in the Brazilian state of Paraíba, known for its preserved architecture and cultural heritage.
-
C.
Talx
Talx is a workforce solutions and employment verification company that operates as a subsidiary of the credit reporting agency Equifax.
-
D.
Aswan granite
Aswan granite is a durable, reddish granite from the Aswan region of Egypt, historically quarried for monumental architecture such as obelisks, statues, and temple elements.
-
E.
Beryl
Beryl is a given name that can be used for people of any gender, historically more common as a female name in English-speaking countries.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb98f5f4881908d9aa0f10be44041 |
completed | March 7, 2026, 5:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae2009951881909d562821fef39c88 |
completed | March 9, 2026, 1:19 a.m. |
| NEDg | Description generation | batch_69ae20fbcd30819099499853d7dc2cc4 |
completed | March 9, 2026, 1:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae216d450c8190ad2ecfdafa2354c7 |
completed | March 9, 2026, 1:25 a.m. |
Created at: March 4, 2026, 7:39 p.m.