Triple

T8406372
Position Surface form Disambiguated ID Type / Status
Subject Jefferson County, Colorado E198509 entity
Predicate contains P35 FINISHED
Object Littleton, Colorado E231909 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: Littleton, Colorado | Statement: [Jefferson County, Colorado, contains, Littleton, Colorado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Littleton, Colorado
Context triple: [Jefferson County, Colorado, contains, Littleton, Colorado]
  • A. Littleton, Colorado chosen
    Littleton, Colorado is a suburban city in the Denver metropolitan area known for its historic downtown, residential neighborhoods, and proximity to the South Platte River.
  • B. Littleton
    Littleton is a suburban town in Middlesex County, Massachusetts, located northwest of Boston.
  • C. Littleton
    Littleton is a village in Surrey, England, known for its proximity to Shepperton and its largely residential, semi-rural character.
  • D. Westminster, Colorado
    Westminster, Colorado is a suburban city in the Denver metropolitan area known for its residential communities, open spaces, and proximity to both Denver and Boulder.
  • E. Englewood, Colorado
    Englewood, Colorado is a suburban city in the Denver metropolitan area known for its mix of residential neighborhoods, commercial centers, and corporate offices.
  • 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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb8312941c8190af0b2def0a4e02be completed March 31, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69cef2e998c48190a112fcf5567f0056 completed April 2, 2026, 10:51 p.m.
Created at: March 30, 2026, 6:05 p.m.