Triple

T15762993
Position Surface form Disambiguated ID Type / Status
Subject Ferenc Csiky E382143 entity
Predicate placeOfBirth P1 FINISHED
Object Pankota E998617 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: Pankota | Statement: [Ferenc Csiky, placeOfBirth, Pankota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pankota
Context triple: [Ferenc Csiky, placeOfBirth, Pankota]
  • A. Pâncota chosen
    Pâncota is a small town in western Romania known for its location in the historical region of Crișana and its surrounding wine-producing areas.
  • B. Parakar
    Parakar is a village in Armenia’s Armavir Province, situated near the capital Yerevan and known for its proximity to Zvartnots International Airport.
  • C. Parkano
    Parkano is a small town and municipality in the Pirkanmaa region of western Finland, known for its forests, lakes, and position along key transport routes.
  • D. Kahuta
    Kahuta is a town in Pakistan’s Punjab province known for hosting the country’s primary nuclear research and enrichment facilities.
  • E. Pennabilli
    Pennabilli is a historic hilltop town in Italy’s Emilia-Romagna region, known for its medieval architecture, scenic Apennine landscapes, and cultural festivals.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b6c9fc8190a1bcf763c4b04b12 completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8776c2488190ad27fd79e2ce4e14 completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 4:47 a.m.