Triple

T7991166
Position Surface form Disambiguated ID Type / Status
Subject E-5 highway E186008 entity
Predicate passesThrough P225 FINISHED
Object Zeytinburnu E653281 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: Zeytinburnu | Statement: [E-5 highway, passesThrough, Zeytinburnu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zeytinburnu
Context triple: [E-5 highway, passesThrough, Zeytinburnu]
  • A. Zeytinburnu chosen
    Zeytinburnu is a densely populated working- and middle-class district on Istanbul’s European side, known as an early industrial area and a key transport hub within the city.
  • B. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • C. Gölbaşı
    Gölbaşı is a district and suburban area of Ankara in central Turkey, known for its lakes, recreational areas, and proximity to the capital city.
  • D. Maltepe
    Maltepe is a residential and commercial district on Istanbul’s Asian side along the Sea of Marmara.
  • E. Sarayönü
    Sarayönü is a rural district and town in central Turkey, located within Konya Province and known for its agricultural activities on the Central Anatolian plateau.
  • 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_69ca829c6c308190ab05b43d234c52b2 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c6fc19c8190b98023e257c2f4f2 completed March 31, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce38d1e5508190abf808fa06f89627 completed April 2, 2026, 9:37 a.m.
Created at: March 30, 2026, 5:16 p.m.