Triple
T31980411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Joe |
E816562
|
entity |
| Predicate | leadActorForCharacter Joe Barrett |
P181172
|
FINISHED |
| Object | Humphrey Bogart |
—
|
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: Humphrey Bogart | Statement: [Tokyo Joe, leadActorForCharacter Joe Barrett, Humphrey Bogart]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorForCharacter Joe Barrett Context triple: [Tokyo Joe, leadActorForCharacter Joe Barrett, Humphrey Bogart]
-
A.
leadActorForCharacter Philip Shayne
Indicates that the specified person is the primary actor portraying the character Philip Shayne.
-
B.
leadActorForCharacter_JeffTravis
Indicates that the referenced person is the lead actor portraying the character Jeff Travis.
-
C.
leadActorForCharacter Steel
Indicates that the specified person is the primary actor portraying the character Steel.
-
D.
leadActorForCharacter David Greene
Indicates that the specified person is the primary actor portraying the character David Greene.
-
E.
leadActorForCharacter Pat Brennan
Indicates that Pat Brennan is the primary performer portraying a particular character in a work.
- 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_69f348f6a3008190bfb59ca695fd68e2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
| PDg | Predicate description generation | batch_69f762651e088190baa21f25378a6065 |
completed | May 3, 2026, 2:57 p.m. |
Created at: May 1, 2026, 12:11 a.m.