Triple

T2300565
Position Surface form Disambiguated ID Type / Status
Subject Texas Panhandle E51719 entity
Predicate hasCounty P285 FINISHED
Object Crane County
Crane County is a sparsely populated county in western Texas known for its oil production and rural desert landscape.
E310573 NE FINISHED

How this triple was built (4 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: Crane County | Statement: [Texas Panhandle, hasCounty, Crane County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Crane County
Context triple: [Texas Panhandle, hasCounty, Crane County]
  • A. Pulaski County
    Pulaski County is a rural county in central Georgia known for its agricultural landscape and the city of Hawkinsville as its county seat.
  • B. Terry County
    Terry County is a rural county in western Texas known for its agriculture, particularly cotton farming, and its location on the South Plains region.
  • C. Stephenson County
    Stephenson County is a county in northern Illinois known for its agricultural landscape, small towns, and historic connection to figures like Jane Addams, who was born in Cedarville.
  • D. Barton County
    Barton County is a rural county in southwestern Missouri, United States, known as the birthplace of President Harry S. Truman.
  • E. Hutchinson County
    Hutchinson County is a rural county in the Texas Panhandle known for its oil and gas production and small, closely knit communities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Crane County
Triple: [Texas Panhandle, hasCounty, Crane County]
Generated description
Crane County is a sparsely populated county in western Texas known for its oil production and rural desert landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Crane County
Target entity description: Crane County is a sparsely populated county in western Texas known for its oil production and rural desert landscape.
  • A. Pulaski County
    Pulaski County is a rural county in central Georgia known for its agricultural landscape and the city of Hawkinsville as its county seat.
  • B. Terry County
    Terry County is a rural county in western Texas known for its agriculture, particularly cotton farming, and its location on the South Plains region.
  • C. Stephenson County
    Stephenson County is a county in northern Illinois known for its agricultural landscape, small towns, and historic connection to figures like Jane Addams, who was born in Cedarville.
  • D. Barton County
    Barton County is a rural county in southwestern Missouri, United States, known as the birthplace of President Harry S. Truman.
  • E. Hutchinson County
    Hutchinson County is a rural county in the Texas Panhandle known for its oil and gas production and small, closely knit communities.
  • F. None of above. chosen

Provenance (5 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_69a88b0a9f248190bcff941463d8f65a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc5edc1348190a4d84606b1310711 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0559d1e708190bc8d28ed3706ae23 completed March 10, 2026, 5:32 p.m.
NEDg Description generation batch_69b0600b4d588190b95be97da3ac0842 completed March 10, 2026, 6:16 p.m.
NED2 Entity disambiguation (via description) batch_69b062a6241c81909f3217a4a33aa4c6 completed March 10, 2026, 6:27 p.m.
Created at: March 4, 2026, 7:49 p.m.