Triple

T10235866
Position Surface form Disambiguated ID Type / Status
Subject Dzibanché E243461 entity
Predicate locatedNear P294 FINISHED
Object Bacalar
Bacalar is a picturesque town in Mexico’s Quintana Roo state, best known for its stunning multi-hued “Lagoon of Seven Colors” and tranquil, less-touristed atmosphere.
 E856724 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: Bacalar | Statement: [Dzibanché, locatedNear, Bacalar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bacalar
Context triple: [Dzibanché, locatedNear, Bacalar]
  • A. Aguadas
    Aguadas is a historic Colombian town in the Caldas Department, known for its coffee culture, traditional hat-making, and well-preserved colonial architecture.
  • B. Bassignana
    Bassignana is a municipality in the Piedmont region of northern Italy, situated near the confluence of the Tanaro and Po rivers.
  • C. Agoncillo
    Agoncillo is a lakeside municipality in the Philippine province of Batangas known for its proximity to Taal Lake and Taal Volcano.
  • D. Cieneguilla
    Cieneguilla is a semi-rural district in the eastern part of Lima, Peru, known for its natural landscapes, country houses, and outdoor recreation areas.
  • E. Requena
    Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
  • 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: Bacalar
Triple: [Dzibanché, locatedNear, Bacalar]
Generated description
Bacalar is a picturesque town in Mexico’s Quintana Roo state, best known for its stunning multi-hued “Lagoon of Seven Colors” and tranquil, less-touristed atmosphere.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bacalar
Target entity description: Bacalar is a picturesque town in Mexico’s Quintana Roo state, best known for its stunning multi-hued “Lagoon of Seven Colors” and tranquil, less-touristed atmosphere.
  • A. Aguadas
    Aguadas is a historic Colombian town in the Caldas Department, known for its coffee culture, traditional hat-making, and well-preserved colonial architecture.
  • B. Bassignana
    Bassignana is a municipality in the Piedmont region of northern Italy, situated near the confluence of the Tanaro and Po rivers.
  • C. Agoncillo
    Agoncillo is a lakeside municipality in the Philippine province of Batangas known for its proximity to Taal Lake and Taal Volcano.
  • D. Cieneguilla
    Cieneguilla is a semi-rural district in the eastern part of Lima, Peru, known for its natural landscapes, country houses, and outdoor recreation areas.
  • E. Requena
    Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d20de15c8190a81f3e9803fdfcd1 completed April 7, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69d74fe436d48190b889ccf5884d1bb7 completed April 9, 2026, 7:06 a.m.
NEDg Description generation batch_69d751122d208190abaa4fd72a07643b completed April 9, 2026, 7:11 a.m.
NED2 Entity disambiguation (via description) batch_69d751d4aa908190a825322ebf0066af completed April 9, 2026, 7:14 a.m.
Created at: April 6, 2026, 11:22 a.m.