Triple

T19638305
Position Surface form Disambiguated ID Type / Status
Subject U.S. Route 80 (Texas) E471460 entity
Predicate passesThrough P225 FINISHED
Object Marshall, Texas 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: Marshall, Texas | Statement: [U.S. Route 80 (Texas), passesThrough, Marshall, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marshall, Texas
Context triple: [U.S. Route 80 (Texas), passesThrough, Marshall, Texas]
  • A. Marshall, Texas chosen
    Marshall, Texas is a small city in East Texas known as a regional cultural and educational center and for its prominence in federal patent litigation.
  • B. Marion, Texas
    Marion, Texas is a small rural town in Guadalupe County within the San Antonio metropolitan area.
  • C. Mart, Texas
    Mart, Texas is a small rural city in Central Texas known for its tight-knit community and agricultural surroundings.
  • D. Martindale, Texas
    Martindale, Texas is a small rural city in Central Texas known for its historic charm and location along the San Marcos River.
  • E. Mabank, Texas
    Mabank, Texas is a small East Texas town near Cedar Creek Lake known for its rural character and proximity to recreational lake activities.
  • 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_69d8e511f28481909f4bc3ea9191e54a completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e641090c408190b2adb8a6abf1b4c9 completed April 20, 2026, 3:06 p.m.
Created at: April 10, 2026, 1:44 p.m.