Triple

T2986830
Position Surface form Disambiguated ID Type / Status
Subject Ankara Metro E80644 entity
Predicate fareMedium P1303 FINISHED
Object Ankarakart
Ankarakart is a contactless smart card used as the primary public transportation payment system in Ankara, Turkey.
 E315532 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: Ankarakart | Statement: [Ankara Metro, fareMedium, Ankarakart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ankarakart
Context triple: [Ankara Metro, fareMedium, Ankarakart]
  • A. Beştepe
    Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
  • B. Ortaköy
    Ortaköy is a lively Bosphorus-side neighborhood in Istanbul known for its waterfront mosque, cafes, and views of the Bosporus Bridge.
  • C. Konak
    Konak is the central historic district of İzmir, Turkey, known for its waterfront, clock tower, and role as the city’s administrative and cultural hub.
  • D. Karaköy
    Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
  • E. Antakya
    Antakya is a city in southern Turkey, historically known as Antioch, renowned as an important center of Hellenistic, Roman, and early Christian civilization.
  • 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: Ankarakart
Triple: [Ankara Metro, fareMedium, Ankarakart]
Generated description
Ankarakart is a contactless smart card used as the primary public transportation payment system in Ankara, Turkey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ankarakart
Target entity description: Ankarakart is a contactless smart card used as the primary public transportation payment system in Ankara, Turkey.
  • A. Beştepe
    Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
  • B. Ortaköy
    Ortaköy is a lively Bosphorus-side neighborhood in Istanbul known for its waterfront mosque, cafes, and views of the Bosporus Bridge.
  • C. Konak
    Konak is the central historic district of İzmir, Turkey, known for its waterfront, clock tower, and role as the city’s administrative and cultural hub.
  • D. Karaköy
    Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
  • E. Antakya
    Antakya is a city in southern Turkey, historically known as Antioch, renowned as an important center of Hellenistic, Roman, and early Christian civilization.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99c88f608190bf734e0b744bf3d1 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108fb46b08190bcbd00e69cf06047 completed March 11, 2026, 6:17 a.m.
NEDg Description generation batch_69b1098429f0819086767078b9687674 completed March 11, 2026, 6:19 a.m.
NED2 Entity disambiguation (via description) batch_69b109ea926481909c85a9aa28027d41 completed March 11, 2026, 6:21 a.m.
Created at: March 8, 2026, 2:59 p.m.