Triple

T9615155
Position Surface form Disambiguated ID Type / Status
Subject Sugar Land Space Cowboys E232199 entity
Predicate city P40 FINISHED
Object Sugar Land E312217 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: Sugar Land | Statement: [Sugar Land Space Cowboys, city, Sugar Land]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sugar Land
Context triple: [Sugar Land Space Cowboys, city, Sugar Land]
  • A. Sugar Land chosen
    Sugar Land is a rapidly growing suburban city in the Houston metropolitan area, known for its master-planned communities, high quality of life, and strong local economy.
  • B. Love Land
    Love Land is an outdoor sculpture park on South Korea’s Jeju Island known for its erotic art and playful, adult-themed exhibits.
  • C. Lone Stars
    The Lone Stars is the nickname of the Liberia national football team, which represents Liberia in international soccer competitions.
  • D. Sweetheart City
    Sweetheart City is a romantic nickname for Loveland, Colorado, known for its Valentine’s Day traditions and heart-themed celebrations.
  • E. Sugar Town
    "Sugar Town" is a 1966 pop song by Nancy Sinatra, known for its light, whimsical style and catchy, laid-back melody.
  • 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_69ca84867bb88190b4b57dd5a56d5691 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9aabb6b88190b53547db885e0129 completed April 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1795e7be08190a088e49a79251570 completed April 4, 2026, 8:49 p.m.
Created at: March 30, 2026, 8:09 p.m.