Triple
T27032976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toprak Ana |
E680972
|
entity |
| Predicate | featuresActorInLeadingRole |
P166850
|
FINISHED |
| Object | Hülya Koçyiğit |
—
|
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: Hülya Koçyiğit | Statement: [Toprak Ana, featuresActorInLeadingRole, Hülya Koçyiğit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresActorInLeadingRole Context triple: [Toprak Ana, featuresActorInLeadingRole, Hülya Koçyiğit]
-
A.
leadRoleActor
chosen
Indicates that an actor performs a leading or principal role in a work or production.
-
B.
filmLeadCharacter
Indicates that a person or character serves as the primary or central protagonist in a film.
-
C.
replacesInLeadRole
Indicates that one entity takes over or substitutes for another entity in the primary or leading role within a given context or production.
-
D.
filmCharacterOf
Indicates that a person or character is a character appearing in a specified film.
-
E.
originalLeadActorRole
Indicates the role originally played by a particular lead actor in a given production or 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_69eeeb5566f08190813daf896fa3da04 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
Created at: April 27, 2026, 7:14 a.m.