Triple

T16992854
Position Surface form Disambiguated ID Type / Status
Subject Iga Province E412235 entity
Predicate hasNotableCity P2813 FINISHED
Object Iga E195170 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: Iga | Statement: [Iga Province, hasNotableCity, Iga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iga
Context triple: [Iga Province, hasNotableCity, Iga]
  • A. Iga chosen
    Iga is a city in Japan historically renowned as one of the principal centers of ninja (shinobi) culture and training.
  • B. Skawa
    Skawa is a river in southern Poland that flows through the Lesser Poland region before joining the Vistula River.
  • C. Morawa
    Morawa is a small rural town in Western Australia known for its grain farming, wildflower displays, and role as a service centre for the surrounding Mid West agricultural region.
  • D. Zawoja
    Zawoja is a large village in southern Poland, known as a popular tourist and hiking base at the foot of Babia Góra in the Beskid Mountains.
  • E. Igo
    Igo is the Japanese name for the ancient strategic board game known internationally as Go, played with black and white stones on a grid to control territory.
  • 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_69d886cb581c8190ab05f4b429c9cd85 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d283d2388190a78bf8d179e83fdc completed April 18, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc16fbdc819095411a056b9942c3 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:32 a.m.