Triple

T17421563
Position Surface form Disambiguated ID Type / Status
Subject Candameña Canyon E423628 entity
Predicate nearbySettlement P350 FINISHED
Object Creel 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: Creel | Statement: [Candameña Canyon, nearbySettlement, Creel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Creel
Context triple: [Candameña Canyon, nearbySettlement, Creel]
  • A. Creel chosen
    Creel is a small mountain town in Mexico’s Sierra Tarahumara that serves as a popular gateway for tourists exploring the Copper Canyon region.
  • B. River Deer
    The River Deer is a small river in Devon, England, that forms part of the local drainage system before joining the River Tamar.
  • C. Snow Creek
    Snow Creek is a small ski and snowboard resort known for its winter sports facilities and family-friendly atmosphere.
  • D. Pike
    Pike is an English surname of Old English origin, often associated with people who lived near a pointed hill or carried a pike as a weapon.
  • E. Kason
    Kason is the second month of the traditional Burmese calendar, associated with religious observances such as the Buddha’s birth, enlightenment, and death anniversaries.
  • 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_69d889d7d27c819088486ce3f0627fa1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e442372954819085f332efc7067ae9 completed April 19, 2026, 2:47 a.m.
Created at: April 10, 2026, 5:46 a.m.