Triple

T3138275
Position Surface form Disambiguated ID Type / Status
Subject Northern Samar E65583 entity
Predicate hasMunicipality P847 FINISHED
Object Lavezares
Lavezares is a coastal municipality in the province of Northern Samar in the Philippines, known for its fishing communities and island landscapes.
 E336041 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: Lavezares | Statement: [Northern Samar, hasMunicipality, Lavezares]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lavezares
Context triple: [Northern Samar, hasMunicipality, Lavezares]
  • A. Yssingeaux
    Yssingeaux is a commune in south-central France that serves as an administrative and service center in the Haute-Loire department.
  • B. Trévélez
    Trévélez is a small Spanish mountain village in the Alpujarras region of Granada, renowned for being one of the highest villages in Spain and for its traditional air-cured ham (jamón).
  • C. Alès
    Alès is a historic industrial town in southern France, located at the foot of the Cévennes mountains.
  • D. La Sarraz
    La Sarraz is a small town in the canton of Vaud, Switzerland, known for its historic castle and role as a cultural and intellectual meeting place.
  • E. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • 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: Lavezares
Triple: [Northern Samar, hasMunicipality, Lavezares]
Generated description
Lavezares is a coastal municipality in the province of Northern Samar in the Philippines, known for its fishing communities and island landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lavezares
Target entity description: Lavezares is a coastal municipality in the province of Northern Samar in the Philippines, known for its fishing communities and island landscapes.
  • A. Yssingeaux
    Yssingeaux is a commune in south-central France that serves as an administrative and service center in the Haute-Loire department.
  • B. Trévélez
    Trévélez is a small Spanish mountain village in the Alpujarras region of Granada, renowned for being one of the highest villages in Spain and for its traditional air-cured ham (jamón).
  • C. Alès
    Alès is a historic industrial town in southern France, located at the foot of the Cévennes mountains.
  • D. La Sarraz
    La Sarraz is a small town in the canton of Vaud, Switzerland, known for its historic castle and role as a cultural and intellectual meeting place.
  • E. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • 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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada574509c81908a88bb10ea35516d completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b24b39d40c8190a5b1a74cfa4caa81 completed March 12, 2026, 5:12 a.m.
NEDg Description generation batch_69b24f37e0608190b968866a9b92364a completed March 12, 2026, 5:29 a.m.
NED2 Entity disambiguation (via description) batch_69b250409a14819087c8879ca9ce6e55 completed March 12, 2026, 5:33 a.m.
Created at: March 8, 2026, 3:05 p.m.