Triple

T8346115
Position Surface form Disambiguated ID Type / Status
Subject Sonja Hogg E196038 entity
Predicate basedIn P40 FINISHED
Object Texas E548 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: Texas | Statement: [Sonja Hogg, basedIn, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Texas
Context triple: [Sonja Hogg, basedIn, Texas]
  • A. Texas chosen
    Texas is the second-largest U.S. state by both area and population, known for its diverse landscapes, major cities like Houston and Dallas, and significant cultural and economic influence.
  • B. Teksas
    Teksas is the famously passionate and vocal supporter group of the Turkish football club Bursaspor, known for its intense atmosphere and choreographies at matches.
  • C. The Texas
    The Texas is a historic steam locomotive famed for its role in the 1862 Great Locomotive Chase during the American Civil War.
  • D. Coahuila y Tejas
    Coahuila y Tejas was a Mexican state in the early 19th century that combined the regions of Coahuila and Texas before Texas’s independence and the formation of the Republic of Texas.
  • E. Oklahoma
    Oklahoma is a landlocked state in the south-central United States known for its Native American heritage, energy industry, and mix of Great Plains and forested landscapes.
  • 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_69ca82edd63c8190b876b8465464c5fa completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7feef7e8819084ca0441d146bac7 completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc6e4eb808190b138c52810f35040 completed April 2, 2026, 1:31 a.m.
Created at: March 30, 2026, 5:58 p.m.