Triple
T36293196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watergate burglars |
E893288
|
entity |
| Predicate | hasParticipantBackground |
P71697
|
FINISHED |
| Object | former CIA officers |
—
|
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: former CIA officers | Statement: [Watergate burglars, hasParticipantBackground, former CIA officers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticipantBackground Context triple: [Watergate burglars, hasParticipantBackground, former CIA officers]
-
A.
hasMemberBackground
chosen
Indicates that an entity has information describing the background or history of one of its members.
-
B.
hasBackground
Indicates that an entity possesses or is associated with a particular background, such as context, setting, or prior circumstances.
-
C.
hasParticipants
Indicates that an event, activity, or situation involves one or more entities as participants in it.
-
D.
hasAuthorBackgroundIn
Indicates that an author possesses a particular background, such as education, experience, or expertise, in a specified field or domain.
-
E.
hasFormerParticipant
Indicates that an entity once participated in an activity, event, or organization but is no longer a current participant.
- 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_69f76e4a61f0819084a2b68dbbb4efc6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0004582bb08190b8d0b88251e8d333 |
completed | May 10, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_6a0003e3e5588190933beea5fb28f150 |
completed | May 10, 2026, 4:04 a.m. |
Created at: May 3, 2026, 4:09 p.m.