Triple

T11954477
Position Surface form Disambiguated ID Type / Status
Subject Hikawa Shrine (Akasaka) E284515 entity
Predicate locatedIn P40 FINISHED
Object Akasaka E235541 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: Akasaka | Statement: [Hikawa Shrine (Akasaka), locatedIn, Akasaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akasaka
Context triple: [Hikawa Shrine (Akasaka), locatedIn, Akasaka]
  • A. Akasaka chosen
    Akasaka is a central Tokyo district known for its business centers, upscale hotels, and vibrant nightlife.
  • B. Shinjuku
    Shinjuku is a major commercial and entertainment district in western Tokyo, known for its busy railway station, skyscrapers, shopping, nightlife, and the Tokyo Metropolitan Government Building.
  • C. Roppongi
    Roppongi is a central Tokyo district famous for its vibrant nightlife, international community, and major art and entertainment complexes.
  • D. Shibuya
    Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
  • E. Aka Akasaka
    Aka Akasaka is a Japanese manga artist and writer best known for creating the hit romantic comedy series "Kaguya-sama: Love Is War."
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90365da288190a132703df563de23 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f74602a7ec8190980e5e6a80aa1235 completed May 3, 2026, 12:56 p.m.
Created at: April 8, 2026, 9:45 p.m.