Triple

T5218347
Position Surface form Disambiguated ID Type / Status
Subject Siargao Island E117807 entity
Predicate hasTown P847 FINISHED
Object Pilar
Pilar is a coastal town on Siargao Island in the Philippines, known for its fishing communities and access to popular surfing and eco-tourism spots.
 E502813 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: [Siargao Island, hasTown, Pilar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pilar
Context triple: [Siargao Island, hasTown, 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. 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.
  • E. Inés
    Inés is a feminine given name, especially common in Spanish-speaking countries, derived from the name Agnes.
  • 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: [Siargao Island, hasTown, Pilar]
Generated description
Pilar is a coastal town on Siargao Island in the Philippines, known for its fishing communities and access to popular surfing and eco-tourism spots.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pilar
Target entity description: Pilar is a coastal town on Siargao Island in the Philippines, known for its fishing communities and access to popular surfing and eco-tourism spots.
  • 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. 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.
  • E. Inés
    Inés is a feminine given name, especially common in Spanish-speaking countries, derived from the name Agnes.
  • 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_69bd4465e03081909bfcfd7113062590 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a96d49c8190a58726a57edebdcc completed March 20, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefebe3b081909f3fe50cf3d73653 completed March 21, 2026, 7:22 p.m.
NEDg Description generation batch_69bef0bfd76c8190ab48fed23b21c70b completed March 21, 2026, 7:25 p.m.
NED2 Entity disambiguation (via description) batch_69bef168c2088190bba7fce5219b0d1f completed March 21, 2026, 7:28 p.m.
Created at: March 20, 2026, 1:48 p.m.