Triple
T8290973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valenton |
E193893
|
entity |
| Predicate | mayor |
P185
|
FINISHED |
| Object |
Metin Yavuz
Metin Yavuz is a French local politician who serves as the mayor of the commune of Valenton in the Île-de-France region.
|
E727379
|
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: Metin Yavuz | Statement: [Valenton, mayor, Metin Yavuz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metin Yavuz Context triple: [Valenton, mayor, Metin Yavuz]
-
A.
Metin Feyzioğlu
Metin Feyzioğlu is a prominent Turkish lawyer, academic, and former president of the Union of Turkish Bar Associations.
-
B.
Metin Oktay
Metin Oktay was a legendary Turkish footballer, best known as a prolific striker and iconic figure for Galatasaray and the Turkish national team in the 1950s and 1960s.
-
C.
Tahsin Banguoğlu
Tahsin Banguoğlu was a Turkish linguist, academic, and politician known for his influential work on Turkish language and grammar.
-
D.
Niyazi Akdaş
Niyazi Akdaş is a Turkish football executive best known for serving as chairman of the Ankara-based club Gençlerbirliği S.K.
-
E.
Tahsin Özgüç
Tahsin Özgüç was a prominent Turkish archaeologist renowned for his pioneering research on ancient Anatolian civilizations.
- 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: Metin Yavuz Triple: [Valenton, mayor, Metin Yavuz]
Generated description
Metin Yavuz is a French local politician who serves as the mayor of the commune of Valenton in the Île-de-France region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Metin Yavuz Target entity description: Metin Yavuz is a French local politician who serves as the mayor of the commune of Valenton in the Île-de-France region.
-
A.
Metin Feyzioğlu
Metin Feyzioğlu is a prominent Turkish lawyer, academic, and former president of the Union of Turkish Bar Associations.
-
B.
Metin Oktay
Metin Oktay was a legendary Turkish footballer, best known as a prolific striker and iconic figure for Galatasaray and the Turkish national team in the 1950s and 1960s.
-
C.
Tahsin Banguoğlu
Tahsin Banguoğlu was a Turkish linguist, academic, and politician known for his influential work on Turkish language and grammar.
-
D.
Niyazi Akdaş
Niyazi Akdaş is a Turkish football executive best known for serving as chairman of the Ankara-based club Gençlerbirliği S.K.
-
E.
Tahsin Özgüç
Tahsin Özgüç was a prominent Turkish archaeologist renowned for his pioneering research on ancient Anatolian civilizations.
- 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_69ca82e32db481908b72f3804fa71152 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7c9b65e0819083ddc82fb7c4a5f3 |
completed | March 31, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc6d38f3c8190a7939e4fd9aff9b6 |
completed | April 2, 2026, 1:30 a.m. |
| NEDg | Description generation | batch_69cdcb8cbd3c8190b467ecbcf55231e9 |
completed | April 2, 2026, 1:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdccff097c819099a33612504468e1 |
completed | April 2, 2026, 1:57 a.m. |
Created at: March 30, 2026, 5:52 p.m.