Triple
T12899133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LaTeX3 |
E308570
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
l3kernel
l3kernel is the core programming layer of LaTeX3, providing the fundamental macros and data structures on which higher-level LaTeX3 code is built.
|
E1008093
|
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: l3kernel | Statement: [LaTeX3, hasComponent, l3kernel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: l3kernel Context triple: [LaTeX3, hasComponent, l3kernel]
-
A.
L3
L3 is a particle physics experiment that operated at CERN’s Large Electron–Positron Collider, designed to study high-energy electron–positron collisions and probe the Standard Model.
-
B.
L3
L3 is one of the main lines of the Barcelona Metro rapid transit system.
-
C.
KERNAL
KERNAL is the low-level operating system and I/O firmware of Commodore 8-bit computers, providing core routines for hardware access and system services.
-
D.
LKO
LKO is the IATA airport code for Chaudhary Charan Singh International Airport serving Lucknow, India.
-
E.
Lively Kernel
Lively Kernel is a web-based, live programming environment and platform for building and manipulating graphical applications directly in the browser using JavaScript and SVG.
- 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: l3kernel Triple: [LaTeX3, hasComponent, l3kernel]
Generated description
l3kernel is the core programming layer of LaTeX3, providing the fundamental macros and data structures on which higher-level LaTeX3 code is built.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: l3kernel Target entity description: l3kernel is the core programming layer of LaTeX3, providing the fundamental macros and data structures on which higher-level LaTeX3 code is built.
-
A.
L3
L3 is a particle physics experiment that operated at CERN’s Large Electron–Positron Collider, designed to study high-energy electron–positron collisions and probe the Standard Model.
-
B.
L3
L3 is one of the main lines of the Barcelona Metro rapid transit system.
-
C.
KERNAL
KERNAL is the low-level operating system and I/O firmware of Commodore 8-bit computers, providing core routines for hardware access and system services.
-
D.
LKO
LKO is the IATA airport code for Chaudhary Charan Singh International Airport serving Lucknow, India.
-
E.
Lively Kernel
Lively Kernel is a web-based, live programming environment and platform for building and manipulating graphical applications directly in the browser using JavaScript and SVG.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9717f3fc48190b61c8f6f36cd0725 |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a56189b081909ed838addcb6d265 |
completed | May 3, 2026, 1:31 a.m. |
| NEDg | Description generation | batch_69f6a6179cdc8190976daa1384032445 |
completed | May 3, 2026, 1:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6a6cbec348190a96a0194b2d6be4b |
completed | May 3, 2026, 1:37 a.m. |
Created at: April 9, 2026, 5:40 p.m.