Triple

T11978652
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Economics and Administrative Sciences, Ege University E285099 entity
Predicate locatedIn P40 FINISHED
Object Bornova E304448 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: Bornova | Statement: [Faculty of Economics and Administrative Sciences, Ege University, locatedIn, Bornova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bornova
Context triple: [Faculty of Economics and Administrative Sciences, Ege University, locatedIn, Bornova]
  • A. Bornova chosen
    Bornova is a populous district of İzmir, Turkey, known for its large university campus, residential neighborhoods, and role as a key suburban hub of the city.
  • B. Bradina
    Bradina is a small village in central Bosnia and Herzegovina, historically notable as the birthplace of Croatian fascist leader Ante Pavelić.
  • C. Bahdini
    Bahdini is a Northern Kurdish dialect spoken primarily in parts of Turkey and Iraq.
  • D. Baniata
    Baniata is an Oceanic language of the Meso-Melanesian group spoken in the Solomon Islands.
  • E. Marcali
    Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90393cfb08190b5b45d3e5e32fad3 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48a9628cc819095d15fd90023e57d completed May 1, 2026, 11:12 a.m.
Created at: April 8, 2026, 9:46 p.m.