Triple
T34494401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennifer Parker (Back to the Future film series) |
E885558
|
entity |
| Predicate | portrayedByInFirstFilm |
P1507
|
FINISHED |
| Object | Claudia Wells |
—
|
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: Claudia Wells | Statement: [Jennifer Parker (Back to the Future film series), portrayedByInFirstFilm, Claudia Wells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedByInFirstFilm Context triple: [Jennifer Parker (Back to the Future film series), portrayedByInFirstFilm, Claudia Wells]
-
A.
portrayedByIn1997Film
Indicates that one entity served as the actor or performer portraying the other entity in a film released in the year 1997.
-
B.
portrayedInFirstTalkingRoleOf
Indicates that an entity portrayed a character in another entity’s first role in a talking (sound) production.
-
C.
portrayedByIn2003Film
Indicates that one entity was portrayed by a particular actor in a film released in 2003.
-
D.
leadActorDebutFilmFor
Indicates that a person’s first film as a lead actor is the specified movie.
-
E.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
- 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_69f349cafcec8190997b45b3fdc16c27 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff136ed2a881908f713401083970d1 |
completed | May 9, 2026, 10:58 a.m. |
| PD | Predicate disambiguation | batch_69ff10f9e3448190b6cb6ea5a67713c1 |
completed | May 9, 2026, 10:48 a.m. |
Created at: May 1, 2026, 2:01 a.m.