Triple
T31792162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CHA |
E811498
|
entity |
| Predicate | hasFormerSection |
P193318
|
FINISHED |
| Object | men's division |
—
|
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: men's division | Statement: [CHA, hasFormerSection, men's division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerSection Context triple: [CHA, hasFormerSection, men's division]
-
A.
hasBackwardsSection
Indicates that an entity contains a segment or portion that is oriented, ordered, or directed in the reverse of the primary or expected direction.
-
B.
hasFormerAnchor
Indicates that an entity previously served as an anchor (e.g., host or main presenter) for another entity, but no longer holds that role.
-
C.
hasSectionOn
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
-
D.
hasStartSection
Indicates that one entity serves as the starting section or initial segment of another entity.
-
E.
isOlderSectionOf
Indicates that one section predates another in time or origin, making it the older of the two.
- 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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
| PDg | Predicate description generation | batch_69fd4128ed908190837ec9936774a1cf |
completed | May 8, 2026, 1:49 a.m. |
Created at: April 30, 2026, 11:39 p.m.