Triple

T19669501
Position Surface form Disambiguated ID Type / Status
Subject T-Com E472295 entity
Predicate associatedWith P37 FINISHED
Object T-Home NE NERFINISHED

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: T-Home | Statement: [T-Com, associatedWith, T-Home]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: T-Home
Context triple: [T-Com, associatedWith, T-Home]
  • A. Tepe Home chosen
    Tepe Home is a Turkish furniture and home décor retail chain offering a wide range of contemporary furnishings and accessories.
  • B. Tenda
    Tenda is a historic mountain village and commune in southeastern France’s Alpes-Maritimes, near the Italian border, known for its medieval architecture and Alpine setting.
  • C. Tuya
    Tuya was an influential queen of Egypt’s 19th Dynasty, best known as the wife of Seti I and the mother of Pharaoh Ramesses II.
  • D. Tiger HAP
    Tiger HAP is a French multi-role attack helicopter variant of the Eurocopter Tiger, optimized for armed reconnaissance and close air support missions.
  • E. T1 International
    T1 International is the international passenger terminal at an airport commonly referred to as Terminal 1.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6416ad1b481908d2890d8c21aac5c completed April 20, 2026, 3:08 p.m.
Created at: April 10, 2026, 1:45 p.m.