Triple
T31534295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keith Broke His Leg |
E804562
|
entity |
| Predicate | starsFictionalizedVersionOf |
P120606
|
FINISHED |
| Object | Keith Powell |
—
|
NE NERFINISHED |
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: Keith Powell | Statement: [Keith Broke His Leg, starsFictionalizedVersionOf, Keith Powell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: starsFictionalizedVersionOf Context triple: [Keith Broke His Leg, starsFictionalizedVersionOf, Keith Powell]
-
A.
filmCharacterVersionOf
Indicates that one character is a specific film adaptation or portrayal of another character originating from a different version or medium.
-
B.
portrayedFictionalVersionOf
chosen
Indicates that one entity depicted or acted as a fictionalized or altered version of another entity.
-
C.
fictionalStandInFor
Indicates that one entity serves as a fictional or symbolic substitute representing another real or implied entity.
-
D.
televisionAdaptationStar
Indicates that a person is a starring actor in a television adaptation of a work.
-
E.
basedOnInFiction
Indicates that a fictional work, character, or element is derived from, inspired by, or modeled after another real or fictional source.
- 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a8055f8081908f635fe04654b5fe |
completed | May 3, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69f6a75656e081908739ed9e2f600e42 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 10:02 p.m.