Triple
T26703274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clara McMillen (Kinsey) |
E673216
|
entity |
| Predicate | filmLeadActorOpposite |
P160108
|
FINISHED |
| Object | Liam Neeson as Alfred Kinsey |
—
|
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: Liam Neeson as Alfred Kinsey | Statement: [Clara McMillen (Kinsey), filmLeadActorOpposite, Liam Neeson as Alfred Kinsey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmLeadActorOpposite Context triple: [Clara McMillen (Kinsey), filmLeadActorOpposite, Liam Neeson as Alfred Kinsey]
-
A.
performedInFilmOpposite
chosen
Indicates that two performers acted together in significant, often directly interacting roles in the same film.
-
B.
associatedWithLeadActorOfFilm
Indicates a relationship where one entity is connected or linked in some relevant way to the lead actor of a specified film.
-
C.
filmCoStar
Indicates that two people appeared together as co-actors in the same film.
-
D.
directorCharacterOf
Indicates that a director is responsible for directing a particular character in a work (e.g., film, TV show, or play).
-
E.
actúaEn
Indicates that an actor or performer takes part in or appears in a specific production, such as a film, play, or television show.
- 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_69eecda2b49c8190a6c481cfc4c07954 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6178140788190b8492b75a2eb7cc4 |
completed | May 2, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 3:32 a.m.