Triple

T4927766
Position Surface form Disambiguated ID Type / Status
Subject Giorgetto Giugiaro E110617 entity
Predicate designedFor P98 FINISHED
Object Subaru E22548 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: Subaru | Statement: [Giorgetto Giugiaro, designedFor, Subaru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Subaru
Context triple: [Giorgetto Giugiaro, designedFor, Subaru]
  • A. Subaru chosen
    Subaru is the Japanese name for the Pleiades star cluster, often associated with unity and prominently used as the brand name and logo motif of a major Japanese automobile manufacturer.
  • B. Mitsubishi Motors
    Mitsubishi Motors is a Japanese automotive manufacturer known for producing a wide range of passenger cars, SUVs, and light commercial vehicles and for its involvement in global automotive alliances.
  • C. Mitsubishi
    Mitsubishi is a major Japanese multinational conglomerate known for its diverse businesses in industries such as automotive, heavy industry, finance, and electronics.
  • D. Nissan
    Nissan is a major Japanese automobile manufacturer known for producing a wide range of passenger cars, trucks, and electric vehicles sold globally.
  • E. Isuzu
    Isuzu is a Japanese automotive manufacturer best known for producing commercial vehicles, pickup trucks, and diesel engines for global markets.
  • 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_69bd4415190c8190817bee7ec9f9f944 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7036d8e88190bc4be2975160da23 completed March 20, 2026, 4:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77ac88148190a51fa2e9085d6897 completed March 21, 2026, 10:49 a.m.
Created at: March 20, 2026, 1:30 p.m.