Triple
T23406635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patrick Denham |
E559951
|
entity |
| Predicate | setsOn |
P152142
|
FINISHED |
| Object | FBI yacht interrogation scene |
—
|
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: FBI yacht interrogation scene | Statement: [Patrick Denham, setsOn, FBI yacht interrogation scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setsOn Context triple: [Patrick Denham, setsOn, FBI yacht interrogation scene]
-
A.
setsOut
Indicates that an entity begins a journey, course of action, or process, moving from an initial state or location toward a goal or destination.
-
B.
setsIn
Indicates that one entity places or positions another entity into or within a specified container, location, or context.
-
C.
setsOutViewOn
Indicates that one entity presents, explains, or articulates its perspective, opinion, or position regarding another entity.
-
D.
sets
Indicates that an entity places, positions, or puts another entity into a particular state, location, or configuration.
-
E.
viewOnSets
Indicates a relationship where one entity holds or defines a particular perspective, interpretation, or stance regarding sets or set-theoretic structures.
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a50e607c8190ba0a22e89862a2d9 |
completed | April 29, 2026, 6:28 a.m. |
| PD | Predicate disambiguation | batch_69f061ed34288190a2e5e8cae03b0095 |
completed | April 28, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f07cbbd7488190ab3c8ae7d0fb68bf |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 17, 2026, 5:38 p.m.