Triple

T16986188
Position Surface form Disambiguated ID Type / Status
Subject San Miguel Department E412070 entity
Predicate contains P35 FINISHED
Object Comacarán
Comacarán is a small municipality and town located in eastern El Salvador.
E1244327 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: Comacarán | Statement: [San Miguel Department, contains, Comacarán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Comacarán
Context triple: [San Miguel Department, contains, Comacarán]
  • A. Lumban
    Lumban is a municipality in the Philippine province of Laguna known for its traditional hand-embroidered textiles and scenic lakeside setting along Laguna de Bay.
  • B. Bolango-Bulango
    Bolango-Bulango is an Austronesian language spoken by the Bolango people in northern Sulawesi, Indonesia.
  • C. Pangcah
    Pangcah is the self-designation of the Amis, one of the largest Indigenous Austronesian peoples of Taiwan, known for their distinct language and rich cultural traditions.
  • D. Palimbang
    Palimbang is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing communities and Moro cultural heritage.
  • E. Kainan
    Kainan is a coastal city in central Wakayama Prefecture, Japan, known for its traditional industries and scenic seaside setting.
  • 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: Comacarán
Triple: [San Miguel Department, contains, Comacarán]
Generated description
Comacarán is a small municipality and town located in eastern El Salvador.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Comacarán
Target entity description: Comacarán is a small municipality and town located in eastern El Salvador.
  • A. Lumban
    Lumban is a municipality in the Philippine province of Laguna known for its traditional hand-embroidered textiles and scenic lakeside setting along Laguna de Bay.
  • B. Bolango-Bulango
    Bolango-Bulango is an Austronesian language spoken by the Bolango people in northern Sulawesi, Indonesia.
  • C. Pangcah
    Pangcah is the self-designation of the Amis, one of the largest Indigenous Austronesian peoples of Taiwan, known for their distinct language and rich cultural traditions.
  • D. Palimbang
    Palimbang is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing communities and Moro cultural heritage.
  • E. Kainan
    Kainan is a coastal city in central Wakayama Prefecture, Japan, known for its traditional industries and scenic seaside setting.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d27b58908190a643bcbd105b1849 completed April 18, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc1109a081908890bbd5958c76c2 completed May 10, 2026, 7:27 p.m.
NEDg Description generation batch_6a0114d5aeb0819086f1a5d279ac0d0f completed May 10, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a0115c583608190bf07ac205399f253 completed May 10, 2026, 11:33 p.m.
Created at: April 10, 2026, 5:32 a.m.