Triple

T7680037
Position Surface form Disambiguated ID Type / Status
Subject Michael Stein E173966 entity
Predicate basedIn P40 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: [Michael Stein, basedIn, Austin, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Austin, Texas
Context triple: [Michael Stein, basedIn, Austin, Texas]
  • A. City of Austin
    The City of Austin is the capital of Texas, known for its vibrant live music scene, tech industry presence, and progressive cultural and political landscape.
  • B. 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.
  • C. Austin
    Austin is one of Chicago’s largest and most populous West Side community areas, known for its historic residential architecture and significant demographic and economic changes over time.
  • D. Austin chosen
    Austin is a major city in central Texas known for its vibrant live music scene, tech industry, and cultural diversity.
  • E. 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.
  • 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_69c6995703e0819081de77361b602e78 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701fe2cc88190b5fd5e1378c32e5b completed March 27, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8eefc58f08190b6d57608a2a296c8 completed March 29, 2026, 9:21 a.m.
Created at: March 27, 2026, 4:01 p.m.