Triple
T33531809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In Pursuit |
E858813
|
entity |
| Predicate | hasNotableActingRoleFor |
P74071
|
FINISHED |
| Object | Claudia Schiffer |
E244317
|
NE FINISHED |
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 Schiffer | Statement: [In Pursuit, hasNotableActingRoleFor, Claudia Schiffer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableActingRoleFor Context triple: [In Pursuit, hasNotableActingRoleFor, Claudia Schiffer]
-
A.
hasPortrayedRole
Indicates that an entity has performed or depicted a specific role or character, typically in a work such as a film, play, or television show.
-
B.
creditedRoleOf
Indicates that a particular role or position is formally acknowledged as being held or performed by a specific entity in a credit or attribution context.
-
C.
hasPortrayedPersonRole
Indicates that an entity has performed or held a specific role in portraying a particular person (e.g., in a film, play, or other representation).
-
D.
actsIn
chosen
Indicates that an entity performs or appears in a creative work, such as a film, play, or show.
-
E.
hasFilmographyIn
Indicates that an individual has participated in or contributed to works within a specified filmography or body of film-related productions.
- F. None of above.
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_69f34978caf4819083f90eba4944d8e8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01c303af6081909c229b2c8e91c680 |
completed | May 11, 2026, 11:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a365c5ed3c881908763d762f1392c6c |
completed | June 20, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_6a01c28ebf54819094318c447d8c7943 |
completed | May 11, 2026, 11:50 a.m. |
Created at: May 1, 2026, 1:39 a.m.