Triple
T33986424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hearts and Minds |
E871423
|
entity |
| Predicate | hasInterviewSubject |
P99527
|
FINISHED |
| Object | General William Westmoreland |
—
|
NE NERFINISHED |
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: General William Westmoreland | Statement: [Hearts and Minds, hasInterviewSubject, General William Westmoreland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInterviewSubject Context triple: [Hearts and Minds, hasInterviewSubject, General William Westmoreland]
-
A.
hasInterviews
chosen
Indicates that one entity conducts, contains, or is associated with interviews involving another entity.
-
B.
usesInterviews
Indicates that one entity employs interviews as a method or tool in relation to another entity or process.
-
C.
hasGivenInterviewsIn
Indicates that an entity has conducted or participated in interviews within a specified place or context.
-
D.
hasGivenNumberOfInterviewsAbout
Indicates that an entity has conducted or participated in a specified number of interviews concerning another entity or topic.
-
E.
hasHumanSubject
Indicates that an entity serves as the human participant or subject involved in an action, event, or relation.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a000be59ad88190a6aa3a42c097796d |
completed | May 10, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_6a000ab6e9bc81908300b81d004e5921 |
completed | May 10, 2026, 4:33 a.m. |
Created at: May 1, 2026, 1:50 a.m.