Triple
T28848424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Williamson |
E728516
|
entity |
| Predicate | portrayedCharacterInFilm |
P54972
|
FINISHED |
| Object | Tommy Gibbs in Black Caesar |
—
|
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: Tommy Gibbs in Black Caesar | Statement: [Fred Williamson, portrayedCharacterInFilm, Tommy Gibbs in Black Caesar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedCharacterInFilm Context triple: [Fred Williamson, portrayedCharacterInFilm, Tommy Gibbs in Black Caesar]
-
A.
characterPortrayedIs
chosen
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
B.
portrayedTitleCharacter
Indicates that one entity played the main or title role character associated with another entity (such as a work or production).
-
C.
filmCharacterOf
Indicates that a person or character is a character appearing in a specified film.
-
D.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
E.
directorCharacterOf
Indicates that a director is responsible for directing a particular character in a work (e.g., film, TV show, or play).
- 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_69f0319f4e5481909e4c439dbe8be940 |
completed | April 28, 2026, 4:03 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, 6:43 a.m.