Triple
T24990291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Who shot J.R.? |
E625427
|
entity |
| Predicate | mainCharacterInvolved |
P39597
|
FINISHED |
| Object | J.R. Ewing |
—
|
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: J.R. Ewing | Statement: [Who shot J.R.?, mainCharacterInvolved, J.R. Ewing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterInvolved Context triple: [Who shot J.R.?, mainCharacterInvolved, J.R. Ewing]
-
A.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
B.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
C.
mainCharactersAre
chosen
Indicates that the specified entities serve as the primary or central characters in a narrative or work.
-
D.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
E.
mainMortalCharacter
Indicates that the referenced entity serves as the primary mortal (non-immortal) character in the context of a story or narrative.
- 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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44a4416e881909c58f3b4d9e4b42d |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 6:03 a.m.