Triple

T20069547
Position Surface form Disambiguated ID Type / Status
Subject Province of Quezon E499696 entity
Predicate hasMunicipality P847 FINISHED
Object Unisan
Unisan is a coastal municipality in the province of Quezon in the Philippines, known for its agricultural economy and rural communities.
 E1410561 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: Unisan | Statement: [Province of Quezon, hasMunicipality, Unisan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Unisan
Context triple: [Province of Quezon, hasMunicipality, Unisan]
  • A. Nisshoki
    Nisshoki, more commonly known as the Hinomaru, is the national flag of Japan featuring a red sun disc centered on a white field.
  • B. Kokusai
    Kokusai was a Japanese aircraft manufacturer known for producing military and transport planes before and during World War II.
  • C. Hakutaka
    Hakutaka is a high-speed train service operating on Japan’s Hokuriku Shinkansen line, connecting Tokyo with cities along the Sea of Japan coast.
  • D. Owariasahi
    Owariasahi is a suburban city in central Japan known for its residential communities and proximity to Nagoya in Aichi Prefecture.
  • E. Chokusaisha
    Chokusaisha are a select group of Shinto shrines distinguished by receiving imperial envoys for special rites, reflecting their high religious and historical importance in Japan.
  • 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: Unisan
Triple: [Province of Quezon, hasMunicipality, Unisan]
Generated description
Unisan is a coastal municipality in the province of Quezon in the Philippines, known for its agricultural economy and rural communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Unisan
Target entity description: Unisan is a coastal municipality in the province of Quezon in the Philippines, known for its agricultural economy and rural communities.
  • A. Nisshoki
    Nisshoki, more commonly known as the Hinomaru, is the national flag of Japan featuring a red sun disc centered on a white field.
  • B. Kokusai
    Kokusai was a Japanese aircraft manufacturer known for producing military and transport planes before and during World War II.
  • C. Hakutaka
    Hakutaka is a high-speed train service operating on Japan’s Hokuriku Shinkansen line, connecting Tokyo with cities along the Sea of Japan coast.
  • D. Owariasahi
    Owariasahi is a suburban city in central Japan known for its residential communities and proximity to Nagoya in Aichi Prefecture.
  • E. Chokusaisha
    Chokusaisha are a select group of Shinto shrines distinguished by receiving imperial envoys for special rites, reflecting their high religious and historical importance in Japan.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e664365ad0819089103b00d1cf8c9f completed April 20, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a081f3acb7881908e23b1d066c35051 completed May 16, 2026, 7:39 a.m.
NEDg Description generation batch_6a081fbb7f208190a032f9f312fd07de completed May 16, 2026, 7:41 a.m.
NED2 Entity disambiguation (via description) batch_6a08208c203c819083abea34d10d5e4e completed May 16, 2026, 7:45 a.m.
Created at: April 11, 2026, 3:39 p.m.