Triple

T2375964
Position Surface form Disambiguated ID Type / Status
Subject Texas's 3rd congressional district E46198 entity
Predicate containsCounty P5971 FINISHED
Object Hunt County
Hunt County is a county in northeastern Texas that includes both rural communities and the city of Greenville as its county seat.
E408957 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: Hunt County | Statement: [Texas's 3rd congressional district, containsCounty, Hunt County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hunt County
Context triple: [Texas's 3rd congressional district, containsCounty, Hunt County]
  • A. Gray County
    Gray County is a rural county in the Texas Panhandle best known for its oil industry and county seat, Pampa.
  • B. Nolan County
    Nolan County is a county in west-central Texas known for its wind energy production and county seat, Sweetwater.
  • C. Dallam County
    Dallam County is a sparsely populated rural county in the far northwestern corner of the Texas Panhandle, known for its agricultural economy and wide-open High Plains landscape.
  • D. Reeves County
    Reeves County is a sparsely populated county in western Texas known for its oil and gas production and desert landscapes.
  • E. McLennan County
    McLennan County is a county in central Texas best known for encompassing the city of Waco, home to Baylor University.
  • 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: Hunt County
Triple: [Texas's 3rd congressional district, containsCounty, Hunt County]
Generated description
Hunt County is a county in northeastern Texas that includes both rural communities and the city of Greenville as its county seat.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hunt County
Target entity description: Hunt County is a county in northeastern Texas that includes both rural communities and the city of Greenville as its county seat.
  • A. Gray County
    Gray County is a rural county in the Texas Panhandle best known for its oil industry and county seat, Pampa.
  • B. Nolan County
    Nolan County is a county in west-central Texas known for its wind energy production and county seat, Sweetwater.
  • C. Dallam County
    Dallam County is a sparsely populated rural county in the far northwestern corner of the Texas Panhandle, known for its agricultural economy and wide-open High Plains landscape.
  • D. Reeves County
    Reeves County is a sparsely populated county in western Texas known for its oil and gas production and desert landscapes.
  • E. McLennan County
    McLennan County is a county in central Texas best known for encompassing the city of Waco, home to Baylor University.
  • 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_69a88a1554a48190a0180682bcf099be completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc794eee481908163148e1e666d9b completed March 7, 2026, 6:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69b555fb4da0819097ee412c9f745afa completed March 14, 2026, 12:35 p.m.
NEDg Description generation batch_69b55718acb88190a491e9654c1f1b7f completed March 14, 2026, 12:39 p.m.
NED2 Entity disambiguation (via description) batch_69b55785a6b4819083737f26eb5db217 completed March 14, 2026, 12:41 p.m.
Created at: March 4, 2026, 7:57 p.m.