Triple
T7614991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cem Karaca |
E172339
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Silvia Karaca
Silvia Karaca is known as the spouse of legendary Turkish rock musician and political activist Cem Karaca.
|
E676013
|
NE FINISHED |
How this triple was built (4 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: Silvia Karaca | Statement: [Cem Karaca, spouse, Silvia Karaca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silvia Karaca Context triple: [Cem Karaca, spouse, Silvia Karaca]
-
A.
Katja Sekerci
Katja Sekerci is the central protagonist of the German drama film "In the Fade," around whom the story of grief, revenge, and the aftermath of a neo-Nazi terrorist attack revolves.
-
B.
Carmen Pavlovic
Carmen Pavlovic is a theatre producer best known for leading the stage adaptation of Baz Luhrmann’s Moulin Rouge! into an award-winning Broadway musical.
-
C.
Célia Šašić
Célia Šašić is a retired German footballer and prolific striker who was one of Europe’s top scorers and a key figure for both the German national team and 1. FFC Frankfurt.
-
D.
Renata Kallosh
Renata Kallosh is a theoretical physicist known for her influential work in supergravity, string theory, and cosmology.
-
E.
Nena Danevic
Nena Danevic is a film editor best known for her Academy Award–winning work on the 1984 historical drama "Amadeus."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Silvia Karaca Triple: [Cem Karaca, spouse, Silvia Karaca]
Generated description
Silvia Karaca is known as the spouse of legendary Turkish rock musician and political activist Cem Karaca.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Silvia Karaca Target entity description: Silvia Karaca is known as the spouse of legendary Turkish rock musician and political activist Cem Karaca.
-
A.
Katja Sekerci
Katja Sekerci is the central protagonist of the German drama film "In the Fade," around whom the story of grief, revenge, and the aftermath of a neo-Nazi terrorist attack revolves.
-
B.
Carmen Pavlovic
Carmen Pavlovic is a theatre producer best known for leading the stage adaptation of Baz Luhrmann’s Moulin Rouge! into an award-winning Broadway musical.
-
C.
Célia Šašić
Célia Šašić is a retired German footballer and prolific striker who was one of Europe’s top scorers and a key figure for both the German national team and 1. FFC Frankfurt.
-
D.
Renata Kallosh
Renata Kallosh is a theoretical physicist known for her influential work in supergravity, string theory, and cosmology.
-
E.
Nena Danevic
Nena Danevic is a film editor best known for her Academy Award–winning work on the 1984 historical drama "Amadeus."
- F. None of above. chosen
Provenance (5 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa4392e881908ed1ab3f64b41600 |
completed | March 27, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8686d16808190bc431c43c0928f6e |
completed | March 28, 2026, 11:46 p.m. |
| NEDg | Description generation | batch_69c8691bf25881909585bb04404f90da |
completed | March 28, 2026, 11:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8698f70a081909633b3b6d7fd45e1 |
completed | March 28, 2026, 11:51 p.m. |
Created at: March 27, 2026, 3:55 p.m.