Triple
T278121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Young Conservatives |
E5292
|
entity |
| Predicate | hasChapters |
P7252
|
FINISHED |
| Object | local branches |
—
|
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: local branches | Statement: [Young Conservatives, hasChapters, local branches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapters Context triple: [Young Conservatives, hasChapters, local branches]
-
A.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
B.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
C.
hasLocalChaptersIn
chosen
Indicates that an organization maintains one or more local chapters or branches within a specified geographic area or location.
-
D.
hasEpisode
Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
-
E.
containsBook
Indicates that one entity (typically a container or collection) includes a specific book as part of its contents.
- F. None of above.
Provenance (3 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dee7830819087f153769a8496b9 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b765f488190b2cbe4b45cd42821 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.