Triple

T18382921
Position Surface form Disambiguated ID Type / Status
Subject Dayton, Texas E446500 entity
Predicate abbreviation P43 FINISHED
Object Dayton, TX 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: Dayton, TX | Statement: [Dayton, Texas, abbreviation, Dayton, TX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dayton, TX
Context triple: [Dayton, Texas, abbreviation, Dayton, TX]
  • A. Dayton, Texas chosen
    Dayton, Texas is a small city in Liberty County that functions as a rural-tinged suburban community within the Greater Houston metropolitan area.
  • B. 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.
  • C. Dorchester, Texas
    Dorchester, Texas is a small rural community located in Grayson County in north-central Texas.
  • D. Dickinson, Texas
    Dickinson, Texas is a small city in Galveston County located between Houston and Galveston along Interstate 45 on the Texas Gulf Coast.
  • E. Tatum, Texas
    Tatum, Texas is a small city in East Texas known for its rural character and location near the intersection of major regional highways.
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5179c931c8190b1c7c8284f42f7b7 completed April 19, 2026, 5:57 p.m.
Created at: April 10, 2026, 10:45 a.m.