Triple

T15973141
Position Surface form Disambiguated ID Type / Status
Subject Liberty E387372 entity
Predicate affiliation P10 FINISHED
Object Adventure City E387378 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: Adventure City | Statement: [Liberty, affiliation, Adventure City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adventure City
Context triple: [Liberty, affiliation, Adventure City]
  • A. Adventure City chosen
    Adventure City is the bustling, high-tech metropolis that serves as the primary urban setting in the animated film "PAW Patrol: The Movie."
  • B. Adventure City
    Adventure City is a small family-oriented amusement park known for its kid-friendly rides and attractions.
  • C. Water City
    Water City is the popular nickname of Liaocheng, a Chinese city renowned for its extensive waterways and historic lakeside scenery.
  • D. Winter City
    Winter City is the popular nickname for Östersund, a Swedish town renowned for its cold climate and strong winter sports culture.
  • E. Golden City
    Golden City is the popular nickname for Jaisalmer, a historic sandstone city in the Thar Desert of Rajasthan, India, famed for its golden-hued fort and architecture.
  • 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_69d86da94ccc819083d187f5dc6a123e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1572a8fd8819092ae1766324b1345 completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3c76c988190a2f2bb4b6ac5ef25 completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:54 a.m.