Triple
T35827947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Pentangeli |
E1035703
|
entity |
| Predicate | laterRecantsTestimony |
P59196
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Frank Pentangeli, laterRecantsTestimony, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterRecantsTestimony Context triple: [Frank Pentangeli, laterRecantsTestimony, true]
-
A.
recantedTestimonyIn
chosen
Indicates that a person has withdrawn or reversed their previous testimony given in a particular case or proceeding.
-
B.
soughtTestimonyAgainst
Indicates that one party actively attempted to obtain another party’s testimony to be used against a specified target in a legal or investigative context.
-
C.
gaveTestimonyIn
Indicates that one entity provided formal testimony or a statement in an official proceeding, event, or context associated with another entity.
-
D.
basedOnTestimonyOf
Indicates that something (such as a claim, decision, or statement) is grounded in, derived from, or justified by the testimony provided by a particular entity.
-
E.
testimonyAffects
Indicates that one party’s testimony has an influence or impact on another entity, situation, or outcome.
- 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_69f76e192a94819082db360cb91e6a8d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00868083b081909afc3d8d4ad56b43 |
completed | May 10, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_6a0084f5f72c8190b08afa82690e322a |
completed | May 10, 2026, 1:15 p.m. |
Created at: May 3, 2026, 4:06 p.m.