Triple

T12805318
Position Surface form Disambiguated ID Type / Status
Subject Konak Ferry Terminal E306129 entity
Predicate operatedBy P86 FINISHED
Object İZDENİZ E307600 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: İZDENİZ | Statement: [Konak Ferry Terminal, operatedBy, İZDENİZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: İZDENİZ
Context triple: [Konak Ferry Terminal, operatedBy, İZDENİZ]
  • A. İZDENİZ chosen
    İZDENİZ is the municipal sea transportation company that operates ferry services within the Gulf of İzmir under the İzmir Metropolitan Municipality.
  • B. İncesu
    İncesu is a town and district in central Turkey known for its historical caravanserai and location within Kayseri Province in Central Anatolia.
  • C. Dizin
    Dizin is one of Iran’s largest and most popular ski resorts, located in the Alborz Mountains north of Tehran.
  • D. Reçak
    Reçak is a village in Kosovo internationally known as the site of the 1999 Račak massacre during the Kosovo War.
  • E. Zellik
    Zellik is a town in the Flemish Brabant province of Belgium, situated just northwest of Brussels and known largely as a residential and light industrial suburb of the capital.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e7f370c8190b3fc39c1b63394c6 completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ec463f08190822e5235362cf584 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:30 p.m.