Triple
T36367336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Hart as Ben Barber |
E895660
|
entity |
| Predicate | relationshipToJamesPayton |
P204845
|
FINISHED |
| Object | future brother-in-law |
—
|
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: future brother-in-law | Statement: [Kevin Hart as Ben Barber, relationshipToJamesPayton, future brother-in-law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToJamesPayton Context triple: [Kevin Hart as Ben Barber, relationshipToJamesPayton, future brother-in-law]
-
A.
relationshipToJimmyChance
Indicates the specific familial, social, or personal connection that an entity has to Jimmy Chance.
-
B.
relationshipToJackiePeyton
Indicates the specific personal, professional, or social relationship that an entity has to Jackie Peyton.
-
C.
relationshipWithSpencerJames
Indicates the existence or nature of a relationship that an entity has with Spencer James.
-
D.
relationshipToJimDear
Indicates a familial, romantic, or otherwise significant personal relationship that an entity has with the person referred to as Jim Dear.
-
E.
relationshipToJamesOIncandenza
Indicates the specific familial, social, or professional relationship that an entity has to James O. Incandenza.
- 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_69f76e5115588190ad8738860b7bc68b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:10 p.m.