Triple

T14503605
Position Surface form Disambiguated ID Type / Status
Subject Pangasinan E340205 entity
Predicate hasMunicipality P847 FINISHED
Object Mapandan
Mapandan is a landlocked agricultural municipality in the province of Pangasinan in the Philippines, known for its rural character and local festivals.
 E1103017 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: Mapandan | Statement: [Pangasinan, hasMunicipality, Mapandan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mapandan
Context triple: [Pangasinan, hasMunicipality, Mapandan]
  • A. Mapanas
    Mapanas is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and Pacific shoreline.
  • B. Menawa
    Menawa was a prominent Creek (Muscogee) leader and war chief who played a key role in resisting U.S. expansion during the early 19th century.
  • C. Mapudungun
    Mapudungun is an indigenous language of South America spoken primarily by the Mapuche people in Chile and Argentina.
  • D. Matabaan
    Matabaan is a town in central Somalia that serves as one of the urban centers within the federal member state of Hirshabelle.
  • E. Mapah
    Mapah is Rabbi Moses Isserles’s glosses on the Shulchan Aruch, integrating Ashkenazi customs and rulings into that foundational Jewish legal code.
  • 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: Mapandan
Triple: [Pangasinan, hasMunicipality, Mapandan]
Generated description
Mapandan is a landlocked agricultural municipality in the province of Pangasinan in the Philippines, known for its rural character and local festivals.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mapandan
Target entity description: Mapandan is a landlocked agricultural municipality in the province of Pangasinan in the Philippines, known for its rural character and local festivals.
  • A. Mapanas
    Mapanas is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and Pacific shoreline.
  • B. Menawa
    Menawa was a prominent Creek (Muscogee) leader and war chief who played a key role in resisting U.S. expansion during the early 19th century.
  • C. Mapudungun
    Mapudungun is an indigenous language of South America spoken primarily by the Mapuche people in Chile and Argentina.
  • D. Matabaan
    Matabaan is a town in central Somalia that serves as one of the urban centers within the federal member state of Hirshabelle.
  • E. Mapah
    Mapah is Rabbi Moses Isserles’s glosses on the Shulchan Aruch, integrating Ashkenazi customs and rulings into that foundational Jewish legal code.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de94e0f9048190a2d266cfa4f9dfb6 completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d9dba1081909154362b922a2417 completed May 8, 2026, 4:59 a.m.
NEDg Description generation batch_69fd6f24431c81908a25ad81c28da56d completed May 8, 2026, 5:05 a.m.
NED2 Entity disambiguation (via description) batch_69fd6ff5a58881909987fa653e58a197 completed May 8, 2026, 5:09 a.m.
Created at: April 10, 2026, 1:21 a.m.