Triple

T585294
Position Surface form Disambiguated ID Type / Status
Subject Marseille E15143 entity
Predicate hasTwinTown P919 FINISHED
Object Kobe E3089 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: Kobe | Statement: [Marseille, hasTwinTown, Kobe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kobe
Context triple: [Marseille, hasTwinTown, Kobe]
  • A. Kobe chosen
    Kobe is a major port city in Japan’s Kansai region, known for its scenic harbor setting, cosmopolitan atmosphere, and famous Kobe beef.
  • B. Hotto Motto Field Kobe
    Hotto Motto Field Kobe is a baseball stadium in Kobe, Japan, known for hosting Nippon Professional Baseball games and serving as a secondary home venue for the Orix Buffaloes.
  • C. Henderson
    Henderson is a major city in the Las Vegas metropolitan area known for its rapid growth, residential communities, and proximity to the Las Vegas Strip.
  • D. Daikanyama
    Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
  • E. Port of Kobe
    The Port of Kobe is one of Japan’s major international seaports, serving as a key hub for container shipping and maritime trade in the Kansai region.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b9874c88190bd1e08d4689ea124 completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a50e25f4e4819081c8973b0f24dec0 completed March 2, 2026, 4:12 a.m.
Created at: March 1, 2026, 7:33 p.m.