Triple

T13352740
Position Surface form Disambiguated ID Type / Status
Subject Ankara commuter rail (Başkentray) E318108 entity
Predicate connects P390 FINISHED
Object Ankara city center E11226 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: Ankara city center | Statement: [Ankara commuter rail (Başkentray), connects, Ankara city center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ankara city center
Context triple: [Ankara commuter rail (Başkentray), connects, Ankara city center]
  • A. Ankara chosen
    Ankara is the political and administrative center of Turkey, known for hosting the country’s government institutions and foreign embassies.
  • B. Etimesgut
    Etimesgut is a rapidly growing suburban district and municipality on the western side of Ankara, Turkey’s capital city.
  • C. Ankara Metropolitan Municipality
    Ankara Metropolitan Municipality is the primary local government authority responsible for administering and providing public services across Turkey’s capital city, Ankara.
  • D. Kayseri
    Kayseri is a historic city in central Turkey, known for its Seljuk and Ottoman architectural heritage and its role as a major commercial and cultural center in Anatolia.
  • E. Çankaya
    Çankaya is a central district of Ankara, Turkey, known for housing key government institutions, foreign embassies, and major national landmarks.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8d520881908aa23c7102b72b72 completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69fde15abe6c8190a6212861bbce790e completed May 8, 2026, 1:12 p.m.
Created at: April 9, 2026, 9:32 p.m.