Triple

T9733378
Position Surface form Disambiguated ID Type / Status
Subject TX-4 E235998 entity
Predicate hasCity P316 FINISHED
Object Greenville, Texas E370621 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: Greenville, Texas | Statement: [TX-4, hasCity, Greenville, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greenville, Texas
Context triple: [TX-4, hasCity, Greenville, Texas]
  • A. Greenville, Texas chosen
    Greenville, Texas is a small city in North Texas that serves as the county seat of Hunt County and a regional hub for commerce and industry.
  • B. Gainesville, Texas
    Gainesville, Texas is a small North Texas city near the Oklahoma border known as the county seat of Cooke County and a regional hub within the Texoma area.
  • C. Groves, Texas
    Groves, Texas is a small city in Jefferson County in Southeast Texas, known as part of the industrial and petrochemical region near Port Arthur and Beaumont.
  • D. New London, Texas
    New London, Texas is a small East Texas town best known as the site of the 1937 New London School explosion, one of the deadliest school disasters in U.S. history.
  • E. Grapevine, Texas
    Grapevine, Texas is a suburban city in North Texas known for its historic downtown, wineries, and proximity to Dallas/Fort Worth International Airport.
  • 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_69ca84d313e88190983ee6ffd0ef60d2 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9eb54fe481908b0202f104b75dc1 completed April 1, 2026, 10:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1afc4dcc4819096d29c1a0529d272 completed April 5, 2026, 12:41 a.m.
Created at: March 30, 2026, 8:22 p.m.