Triple
T34595160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | stddef.h |
E888287
|
entity |
| Predicate | macroCategory |
P179746
|
FINISHED |
| Object | null pointer constant macro |
—
|
LITERAL FINISHED |
How this triple was built (2 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: null pointer constant macro | Statement: [stddef.h, macroCategory, null pointer constant macro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: macroCategory Context triple: [stddef.h, macroCategory, null pointer constant macro]
-
A.
canonicalCategory
Indicates that an entity is assigned to its primary or standard category within a classification system.
-
B.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
C.
coreCategory
Indicates that one entity is the primary or fundamental category to which another entity belongs or is classified under.
-
D.
textCategory
Indicates that a piece of text belongs to or is classified under a particular category or type.
-
E.
categoryLabel_N
Indicates that an entity is assigned a specific categorical label or classification name.
- F. None of above. chosen
Provenance (4 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_69f349d3bfcc81909874c99e646fb3ea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f727bde8f88190ad746ca515134ca1 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72739c30c81908642eef3feb3afcf |
completed | May 3, 2026, 10:45 a.m. |
| PDg | Predicate description generation | batch_69f727bd39b081908457590c3ba9b745 |
completed | May 3, 2026, 10:47 a.m. |
Created at: May 1, 2026, 2:03 a.m.