Triple
T36608940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 14 Women |
E903114
|
entity |
| Predicate | hasNumberOfMainSubjects |
P103965
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [14 Women, hasNumberOfMainSubjects, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMainSubjects Context triple: [14 Women, hasNumberOfMainSubjects, 14]
-
A.
hasPrimarySubject
Indicates that an entity is the main or principal subject associated with another entity or resource.
-
B.
hasMainSubjectKey
Indicates that an entity is associated with a primary or principal subject identifier used as its main reference or key.
-
C.
hasSubjectCount
chosen
Indicates that an entity is associated with a specific number of subjects.
-
D.
hasSecondarySubject
Indicates that an entity is associated with an additional, non-primary subject in a given context or relationship.
-
E.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff1ba8694481909ceb36f26ca85612 |
completed | May 9, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69ff1b27f0f08190a9e74308c5b3d1ba |
completed | May 9, 2026, 11:31 a.m. |
Created at: May 3, 2026, 4:11 p.m.