Triple
T21526932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Vagina Monologues |
E531120
|
entity |
| Predicate | numberOfInterviews |
P144716
|
FINISHED |
| Object | over 200 |
—
|
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: over 200 | Statement: [The Vagina Monologues, numberOfInterviews, over 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInterviews Context triple: [The Vagina Monologues, numberOfInterviews, over 200]
-
A.
hasGivenNumberOfInterviewsAbout
Indicates that an entity has conducted or participated in a specified number of interviews concerning another entity or topic.
-
B.
hasInterviews
Indicates that one entity conducts, contains, or is associated with interviews involving another entity.
-
C.
usesInterviews
Indicates that one entity employs interviews as a method or tool in relation to another entity or process.
-
D.
numberOfSurveyPoints
Indicates the total count of survey points associated with a given entity or context.
-
E.
numberOfInvestigations
Indicates the count of investigations associated with or conducted by a given entity.
- 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_69e0c45d95a081908e7962ad215da746 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee88515874819085e251c0d297a587 |
completed | April 26, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69e6320043bc81909417c41a718652ba |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e6386c5a4481909c37f7de7e9fc025 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 16, 2026, 6:26 p.m.