Triple
T30007292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Hayden (Tommy Boy) |
E762359
|
entity |
| Predicate | relationshipTypeWithTommy Callahan III |
P203762
|
FINISHED |
| Object | reluctant partner |
—
|
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: reluctant partner | Statement: [Richard Hayden (Tommy Boy), relationshipTypeWithTommy Callahan III, reluctant partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithTommy Callahan III Context triple: [Richard Hayden (Tommy Boy), relationshipTypeWithTommy Callahan III, reluctant partner]
-
A.
relationshipTypeWithTommyAlbright
Indicates the specific nature or category of the relationship an entity has with Tommy Albright.
-
B.
relationshipTypeWithHayleyTravis
Indicates the specific nature or category of the relationship that an entity has with Hayley Travis.
-
C.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
D.
relationshipTypeWith Dolly Talbo
Indicates the specific nature or category of the relationship that an entity has with Dolly Talbo.
-
E.
relationshipToProfessorCallahan
Indicates the type or nature of a person's relationship or connection to Professor Callahan.
- 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_69f2246a47ac81909cf5213053687ffc |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a01e993fec0819090cc397218515e88 |
completed | May 11, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_6a01e57594188190a2354f48cf71b48c |
completed | May 11, 2026, 2:19 p.m. |
| PDg | Predicate description generation | batch_6a01e9930c848190bf39a09cd0f4af2e |
completed | May 11, 2026, 2:37 p.m. |
Created at: April 29, 2026, 6:43 p.m.