Triple

T2979510
Position Surface form Disambiguated ID Type / Status
Subject Province of Bataan E80476 entity
Predicate contains P35 FINISHED
Object Pilar
Pilar is a coastal municipality in the Philippine province of Bataan known for its historical significance in World War II and its role in the defense of Bataan.
 E320137 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: Pilar | Statement: [Province of Bataan, contains, Pilar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pilar
Context triple: [Province of Bataan, contains, Pilar]
  • A. Pilar
    Pilar is a strong-willed, perceptive Spanish guerrilla fighter who plays a central role in Ernest Hemingway’s novel "For Whom the Bell Tolls."
  • B. Pilar
    Pilar is a riverside city in southwestern Paraguay known for its colonial architecture, river port activities, and proximity to the border with Argentina.
  • C. Pilar
    Pilar is the introspective female protagonist of Paulo Coelho’s novel "By the River Piedra I Sat Down and Wept," whose spiritual and emotional journey drives the story.
  • D. Fernanda
    Fernanda is a feminine given name commonly used in Romance-language countries, derived from the masculine name Ferdinand.
  • E. Amparo
    Amparo is a municipality in the interior of Brazil known for its historical architecture and role in the coffee-producing region of the state of São Paulo.
  • 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: Pilar
Triple: [Province of Bataan, contains, Pilar]
Generated description
Pilar is a coastal municipality in the Philippine province of Bataan known for its historical significance in World War II and its role in the defense of Bataan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pilar
Target entity description: Pilar is a coastal municipality in the Philippine province of Bataan known for its historical significance in World War II and its role in the defense of Bataan.
  • A. Pilar
    Pilar is a strong-willed, perceptive Spanish guerrilla fighter who plays a central role in Ernest Hemingway’s novel "For Whom the Bell Tolls."
  • B. Pilar
    Pilar is a riverside city in southwestern Paraguay known for its colonial architecture, river port activities, and proximity to the border with Argentina.
  • C. Pilar
    Pilar is the introspective female protagonist of Paulo Coelho’s novel "By the River Piedra I Sat Down and Wept," whose spiritual and emotional journey drives the story.
  • D. Fernanda
    Fernanda is a feminine given name commonly used in Romance-language countries, derived from the masculine name Ferdinand.
  • E. Amparo
    Amparo is a municipality in the interior of Brazil known for its historical architecture and role in the coffee-producing region of the state of São Paulo.
  • 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_69ad8b15f6ac8190be5fd16a33edcb4f completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad999cca40819082e2d6d10bdb7872 completed March 8, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1de999ff88190824ecdc164496d37 completed March 11, 2026, 9:28 p.m.
NEDg Description generation batch_69b1df61bb208190b7714ff14ff81a99 completed March 11, 2026, 9:32 p.m.
NED2 Entity disambiguation (via description) batch_69b1dfd8fc5481908f1e130226d606fb completed March 11, 2026, 9:34 p.m.
Created at: March 8, 2026, 2:58 p.m.