Triple

T5066896
Position Surface form Disambiguated ID Type / Status
Subject Lyon tramway line T4 E114165 entity
Predicate partOf P40 FINISHED
Object TCL network E487436 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: TCL network | Statement: [Lyon tramway line T4, partOf, TCL network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TCL network
Context triple: [Lyon tramway line T4, partOf, TCL network]
  • A. TCL chosen
    TCL is the public transport network operator serving Lyon and its metropolitan area in France, managing buses, trams, and metro services.
  • B. TCL Corporation
    TCL Corporation is a major Chinese electronics company best known globally for manufacturing televisions and other consumer electronics.
  • C. T-Com
    T-Com is a telecommunications brand associated with Deutsche Telekom, known for providing mobile and fixed-line communication services and sponsoring major sports venues.
  • D. ZTE
    ZTE is a major Chinese telecommunications and technology company known for manufacturing network equipment and smartphones and competing globally with firms like Nokia and Huawei.
  • E. TVS Television Network
    TVS Television Network was an American syndicated sports television network known for broadcasting a wide range of live sporting events and special programming from the 1960s through the 1980s.
  • 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_69bd443c0c8c81908663b77afb28e165 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd749bf69c819093e75dce56f1c0ab completed March 20, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea49d917081909ead17eed3f8af90 completed March 21, 2026, 2:01 p.m.
Created at: March 20, 2026, 1:38 p.m.