Triple

T2656821
Position Surface form Disambiguated ID Type / Status
Subject Manneken Pis E54630 entity
Predicate hasReplica P103 FINISHED
Object Tokyo E5560 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: Tokyo | Statement: [Manneken Pis, hasReplica, Tokyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo
Context triple: [Manneken Pis, hasReplica, Tokyo]
  • A. Tokyo chosen
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • B. Tōkyō-wan
    Tōkyō-wan is the Japanese name for Tokyo Bay, a major urban bay on the Pacific coast of Honshu that serves as a key economic and transportation hub for the Greater Tokyo Area.
  • C. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • D. Kyoto
    Kyoto is a historic Japanese city renowned for its well-preserved temples, traditional wooden houses, and role as the former imperial capital.
  • E. Ōta, Tokyo
    Ōta, Tokyo is a large ward in southern Tokyo known for its mix of residential and industrial areas and for hosting Haneda Airport, one of Japan’s major international gateways.
  • 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_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd94ae2e881909399b3d58159aa29 completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc25d9348190a216c53d1c7f8820 completed March 11, 2026, 5:22 a.m.
Created at: March 6, 2026, 9:53 p.m.