Triple

T8591732
Position Surface form Disambiguated ID Type / Status
Subject Masku E203442 entity
Predicate administrativeCenter P1474 FINISHED
Object Masku (urban area) E203442 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: Masku (urban area) | Statement: [Masku, administrativeCenter, Masku (urban area)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masku (urban area)
Context triple: [Masku, administrativeCenter, Masku (urban area)]
  • A. Masku municipality chosen
    Masku municipality is a small local government area in Southwest Finland known for its rural landscapes and proximity to the city of Turku.
  • B. Miyapur
    Miyapur is a rapidly developing residential and commercial suburb in the northwestern part of Hyderabad, India.
  • C. Modasa
    Modasa is a town in the Indian state of Gujarat that serves as the administrative headquarters of Aravalli district.
  • D. Honmoku area
    The Honmoku area is a coastal district in Yokohama, Japan, known for its historic port-related development and cultural sites such as the traditional Japanese landscape of Sankeien Garden.
  • E. Vashi
    Vashi is a major suburban railway station and commercial-residential hub in Navi Mumbai, India.
  • 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_69ca832a7f108190b4e4f5648abf4aa2 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc466747b88190b752f78f361140cb completed March 31, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8b584088190bc5b8b2785894d82 completed April 2, 2026, 5:34 p.m.
Created at: March 30, 2026, 6:23 p.m.