Triple

T9723828
Position Surface form Disambiguated ID Type / Status
Subject Angoulême E235549 entity
Predicate twinnedWith P1072 FINISHED
Object Turda E358030 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: Turda | Statement: [Angoulême, twinnedWith, Turda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turda
Context triple: [Angoulême, twinnedWith, Turda]
  • A. Turda chosen
    Turda is a historic town in central Romania’s Transylvania region, known for its ancient salt mine and significant Roman and medieval heritage.
  • B. Tivissa
    Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
  • C. Tura
    Tura is a prominent town in the Indian state of Meghalaya, serving as a major administrative, cultural, and economic center in the Garo Hills region.
  • D. Tura
    Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
  • E. Tarusa
    Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
  • 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_69ca84d0123c819096f9dc3b6abb0881 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e77096481908ffd315fecb1d5ec completed April 1, 2026, 10:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19faa064081909c1d23044984a17c completed April 4, 2026, 11:32 p.m.
Created at: March 30, 2026, 8:21 p.m.