Triple

T15204446
Position Surface form Disambiguated ID Type / Status
Subject Llano County E363353 entity
Predicate seat P75 FINISHED
Object Llano
Llano is a small central Texas city known for its historic courthouse square, scenic location on the Llano River, and role as a gateway to the Texas Hill Country.
 E1143880 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: Llano | Statement: [Llano County, seat, Llano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Llano
Context triple: [Llano County, seat, Llano]
  • A. Llano Blanco
    Llano Blanco is a small settlement located within the municipality of El Rosario in Mexico.
  • B. Madera
    Madera is a city in California’s San Joaquin Valley known primarily as the administrative and economic center of Madera County.
  • C. El Caney
    El Caney is a village near Santiago de Cuba that was the site of a major and fiercely contested battle during the Spanish–American War.
  • D. Claro Valley
    Claro Valley is a subregion within Chile’s Maule Valley wine region, known for producing a range of quality wines influenced by its diverse microclimates and soils.
  • E. La Trinidad Valley
    La Trinidad Valley is a fertile highland valley in the Philippine province of Benguet known for its cool climate, vegetable farms, and strawberry fields.
  • 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: Llano
Triple: [Llano County, seat, Llano]
Generated description
Llano is a small central Texas city known for its historic courthouse square, scenic location on the Llano River, and role as a gateway to the Texas Hill Country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Llano
Target entity description: Llano is a small central Texas city known for its historic courthouse square, scenic location on the Llano River, and role as a gateway to the Texas Hill Country.
  • A. Llano Blanco
    Llano Blanco is a small settlement located within the municipality of El Rosario in Mexico.
  • B. Madera
    Madera is a city in California’s San Joaquin Valley known primarily as the administrative and economic center of Madera County.
  • C. El Caney
    El Caney is a village near Santiago de Cuba that was the site of a major and fiercely contested battle during the Spanish–American War.
  • D. Claro Valley
    Claro Valley is a subregion within Chile’s Maule Valley wine region, known for producing a range of quality wines influenced by its diverse microclimates and soils.
  • E. La Trinidad Valley
    La Trinidad Valley is a fertile highland valley in the Philippine province of Benguet known for its cool climate, vegetable farms, and strawberry fields.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006b693a48190a6230b7b52bc8cd3 completed April 15, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed33b911c8190815341a342a8d3c8 completed May 9, 2026, 6:24 a.m.
NEDg Description generation batch_69fed744f8b48190948d42a8da9d2e70 completed May 9, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_69fed7d9934c8190bd2d00830e5d33bb completed May 9, 2026, 6:44 a.m.
Created at: April 10, 2026, 3:11 a.m.