Triple

T16151130
Position Surface form Disambiguated ID Type / Status
Subject European side of Istanbul E391910 entity
Predicate hasPart P35 FINISHED
Object Avcılar E688496 NE 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: Avcılar | Statement: [European side of Istanbul, hasPart, Avcılar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Avcılar
Context triple: [European side of Istanbul, hasPart, Avcılar]
  • A. Avcılar chosen
    Avcılar is a district on the European side of Istanbul, Turkey, known for its residential areas, university campus, and location along the Marmara Sea.
  • B. Bahçelievler
    Bahçelievler is a densely populated residential and commercial district on the European side of Istanbul, Turkey.
  • C. Bahçelievler
    Bahçelievler is a residential neighborhood located within the Karşıyaka district of İzmir, Turkey.
  • D. Sultanbeyli
    Sultanbeyli is a densely populated, predominantly residential district on the Asian side of Istanbul, known for its rapid urbanization and working-class character.
  • E. Karacabey
    Karacabey is a town and district in northwestern Turkey known for its agriculture and proximity to both the Marmara Sea and the city of Bursa.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21d981950819087fdacc7879dca97 completed April 17, 2026, 11:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a001f83f6ac8190b9f18fe701a9b3ce completed May 10, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:01 a.m.