Triple

T15446495
Position Surface form Disambiguated ID Type / Status
Subject Hatanodai E370034 entity
Predicate hasNearbyArea P4647 FINISHED
Object Ebara E364440 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: Ebara | Statement: [Hatanodai, hasNearbyArea, Ebara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ebara
Context triple: [Hatanodai, hasNearbyArea, Ebara]
  • A. Ebara chosen
    Ebara is a district within Tokyo’s Shinagawa ward, known as a primarily residential area with local shopping streets and traditional neighborhoods.
  • B. Sanyo-Onoda
    Sanyo-Onoda is a coastal industrial city in western Japan known for its cement and chemical industries and its location along the Seto Inland Sea.
  • C. Mibuchi
    Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
  • D. Nissho
    Nissho was a prominent disciple of the Japanese Buddhist monk Nichiren who helped propagate and systematize Nichiren Buddhism.
  • E. Kawada Industries
    Kawada Industries is a Japanese engineering and construction company known for its work on major infrastructure projects, including prominent bridges and civil works.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef767b4819099f2c0919a158321 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21adb6b88190b573068bda223892 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:21 a.m.