Triple

T13855144
Position Surface form Disambiguated ID Type / Status
Subject Little Big Town E333044 entity
Predicate album P1995 FINISHED
Object Tornado E1066834 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: Tornado | Statement: [Little Big Town, album, Tornado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tornado
Context triple: [Little Big Town, album, Tornado]
  • A. Tornado
    Tornado is a high-thrill water slide attraction featuring steep drops and a large funnel element, located at the Wet'n'Wild Gold Coast water park in Australia.
  • B. Tornado
    Tornado is a high-performance Python web framework and asynchronous networking library designed for handling large numbers of simultaneous connections.
  • C. Tornado
    The Tornado is a twin-engine, variable-sweep wing multirole combat aircraft developed jointly by the United Kingdom, Germany, and Italy, used for strike, reconnaissance, and electronic warfare missions.
  • D. Tornado
    Tornado is Zorro’s iconic black horse, known as his swift and loyal steed in the Zorro stories.
  • E. Tornado chosen
    "Tornado" is a country music song by Little Big Town known for its dark, storm-themed metaphor and distinctive vocal harmonies.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02db9c9c81909bb2d2fbfb7394b1 completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c70a59e8819090b750699993a107 completed May 3, 2026, 10:07 p.m.
Created at: April 9, 2026, 10:14 p.m.