Triple
T28044826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dobbs |
E708649
|
entity |
| Predicate | filmVersionName |
P50342
|
FINISHED |
| Object | Fred C. Dobbs |
—
|
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: Fred C. Dobbs | Statement: [Dobbs, filmVersionName, Fred C. Dobbs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmVersionName Context triple: [Dobbs, filmVersionName, Fred C. Dobbs]
-
A.
movieVariantName
chosen
Indicates that one movie is known by an alternative or variant name (such as a translated, regional, or re-release title).
-
B.
notableFilmVersion
Indicates that one work is a film adaptation or version of another work that is considered particularly notable or significant.
-
C.
filmCharacterVersionOf
Indicates that one character is a specific film adaptation or portrayal of another character originating from a different version or medium.
-
D.
versionUsedInFilm
Indicates that a particular version or edition of a work is the one that was used in a specific film.
-
E.
televisionVersionName
Indicates the specific name or title assigned to a particular version or edition of a television-related work.
- 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_69ef9b6cf538819094a633ffa67afec1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f63f335bb8819086d6397da14befd0 |
completed | May 2, 2026, 6:15 p.m. |
| PD | Predicate disambiguation | batch_69f63710d17c819084cfe96e6df334fd |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 8:28 p.m.