Triple
T907738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chair O |
E19586
|
entity |
| Predicate | isNumbered |
P22578
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chair O, isNumbered, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNumbered Context triple: [Chair O, isNumbered, true]
-
A.
isSectionNumber
Indicates that one entity is the section number identifier associated with another entity, typically within a structured document or text.
-
B.
hasCategoryNumbering
Indicates that an entity is assigned or associated with a specific category-based numbering or index within a classification system.
-
C.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
D.
titleNumber
Indicates the numerical designation or sequence number assigned to a title within an ordered set of titles.
-
E.
frontNumbering
Indicates that an entity is assigned a numbering or label that appears at the front or beginning of something (e.g., a sequence, document, or list).
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3bcad2481908b83575b2fb80d14 |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b28ff5948190982c4439eadf9d87 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b3bab5788190a62a0e23a698f7c7 |
completed | March 1, 2026, 9:46 p.m. |
Created at: March 1, 2026, 7:39 p.m.