Triple
T28638714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harsh Times |
E724860
|
entity |
| Predicate | characterPlayedBy_Christian Bale |
P9616
|
FINISHED |
| Object | Jim Luther Davis |
—
|
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: Jim Luther Davis | Statement: [Harsh Times, characterPlayedBy_Christian Bale, Jim Luther Davis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedBy_Christian Bale Context triple: [Harsh Times, characterPlayedBy_Christian Bale, Jim Luther Davis]
-
A.
characterPlayedByRichardHarris
Indicates that the subject is a character that was portrayed by the actor Richard Harris.
-
B.
playedBy
chosen
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
C.
hasTimothyDaltonRole
Indicates that an entity holds or is associated with a role played by Timothy Dalton.
-
D.
characterPlayedByGeneHackman
Indicates that a given character is portrayed or acted by Gene Hackman.
-
E.
worksForCharacterPlayedBy
Indicates that one character is employed by, or works under, another character who is portrayed by a specific actor.
- 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_69f01d8328c48190bc0e5f9b9b848582 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
Created at: April 28, 2026, 4:42 a.m.