Triple

T1985463
Position Surface form Disambiguated ID Type / Status
Subject Kay Bailey Hutchison E43128 entity
Predicate workLocation P7 FINISHED
Object Austin, Texas E15420 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: Austin, Texas | Statement: [Kay Bailey Hutchison, workLocation, Austin, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Austin, Texas
Context triple: [Kay Bailey Hutchison, workLocation, Austin, Texas]
  • A. Dallas, Texas
    Dallas, Texas is a major metropolitan city in northern Texas known for its role as a commercial and cultural hub, particularly in finance, technology, and telecommunications.
  • B. Austin
    Austin is a small historic mining town in central Nevada known for its 19th-century silver boom and remote, high-desert setting along U.S. Route 50.
  • C. Austin chosen
    Austin is a major city in central Texas known for its vibrant live music scene, tech industry, and cultural diversity.
  • D. Frisco, Texas
    Frisco, Texas is a rapidly growing suburban city in the Dallas–Fort Worth metropolitan area known for its sports venues, retail centers, and family-friendly communities.
  • E. San Antonio
    San Antonio is a coastal municipality in the Philippine province of Zambales known for its beaches, coves, and nearby island-hopping destinations.
  • 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb821c2d48190abea6c89f37b51b1 completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69becf8388f8819090829c206f4080a2 completed March 21, 2026, 5:04 p.m.
Created at: March 4, 2026, 7:37 p.m.