Triple

T5395638
Position Surface form Disambiguated ID Type / Status
Subject E120647 entity
Predicate reading P63726 FINISHED
Object Subaru E22548 NE FINISHED

How this triple was built (3 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: [昴, reading, Subaru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Subaru
Context triple: [昴, reading, 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.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: reading
Context triple: [昴, reading, Subaru]
  • A. readingAid
    Indicates that one entity assists or facilitates another entity’s ability to read or engage in reading activities.
  • B. readingFeature
    Indicates that an entity possesses a characteristic, capability, or attribute specifically related to reading.
  • C. readingExperience
    Indicates the relationship in which an entity engages with written or visual material, capturing the act, manner, or quality of that reading activity.
  • D. containsReading
    Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
  • E. readership
    Indicates the relationship in which one party reads, follows, or is the audience for the written or published work of another.
  • F. None of above. chosen

Provenance (5 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_69bd4637b92c8190b815b6443ae4b323 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd8932b8bc8190bd31e11b167a7212 completed March 20, 2026, 5:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf33739e388190b7d8d27484d7b269 completed March 22, 2026, 12:10 a.m.
PD Predicate disambiguation batch_69bd84660ea08190a641084814fcf94d completed March 20, 2026, 5:31 p.m.
PDg Predicate description generation batch_69bd8931302c81908afcb0f011e91f09 completed March 20, 2026, 5:51 p.m.
Created at: March 20, 2026, 2:04 p.m.