Triple

T3364877
Position Surface form Disambiguated ID Type / Status
Subject Chiyoda E70810 entity
Predicate contains P35 FINISHED
Object Kanda district E415529 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: Kanda district | Statement: [Chiyoda, contains, Kanda district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanda district
Context triple: [Chiyoda, contains, Kanda district]
  • A. Kanda district chosen
    Kanda district is a historic commercial and cultural area in central Tokyo known for its old bookstores, electronics shops, and traditional shrines.
  • B. Tenma district
    Tenma district is a bustling urban neighborhood in Osaka, Japan, known for its traditional shopping arcades, lively nightlife, and historic Tenmangu Shrine.
  • C. Kaifu District
    Kaifu District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
  • D. Tsuzuki District
    Tsuzuki District is a former administrative district that once existed within Kyoto Prefecture in Japan.
  • E. Namba district
    Namba district is a major entertainment and shopping area in Osaka, Japan, known for its neon lights, bustling nightlife, and iconic landmarks.
  • 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_69ad85a729d48190afd789cd8417f289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb28643f48190b78b0222f8323344 completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bde0234b6481908dcf37da32cf856b completed March 21, 2026, 12:02 a.m.
Created at: March 8, 2026, 3:13 p.m.