Triple
T34232442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niv Sultan |
E878236
|
entity |
| Predicate | characterOccupationOfPortrayedRole |
P153983
|
FINISHED |
| Object | Mossad agent |
—
|
LITERAL 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: Mossad agent | Statement: [Niv Sultan, characterOccupationOfPortrayedRole, Mossad agent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterOccupationOfPortrayedRole Context triple: [Niv Sultan, characterOccupationOfPortrayedRole, Mossad agent]
-
A.
portrayedProfessionOfCharacter
chosen
Indicates that one entity is the profession or occupation depicted as being held by a particular character.
-
B.
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).
-
C.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
D.
directorPortraysCharacter
Indicates that a film director personally appears in a work portraying a specific character.
-
E.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
- 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_69f349b22d8c819096b22df268382aa9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff63225b6481909217ad11b4f7d3ba |
completed | May 9, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69ff60e0882c819085d097010db43ee0 |
completed | May 9, 2026, 4:29 p.m. |
Created at: May 1, 2026, 1:56 a.m.