Triple

T13352778
Position Surface form Disambiguated ID Type / Status
Subject M2 line E318109 entity
Predicate fareSystem P395 FINISHED
Object AnkaraKart E315532 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: AnkaraKart | Statement: [M2 line, fareSystem, AnkaraKart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AnkaraKart
Context triple: [M2 line, fareSystem, AnkaraKart]
  • A. Ankarakart chosen
    Ankarakart is a contactless smart card used as the primary public transportation payment system in Ankara, Turkey.
  • B. Ankara city bus network
    The Ankara city bus network is the primary urban bus system serving Turkey’s capital, connecting neighborhoods, landmarks, and suburbs through an extensive network of routes.
  • 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. Etimesgut
    Etimesgut is a rapidly growing suburban district and municipality on the western side of Ankara, Turkey’s capital city.
  • 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_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_69f71f49e5548190b14d09daea628e6b completed May 3, 2026, 10:11 a.m.
Created at: April 9, 2026, 9:32 p.m.