Triple

T12504735
Position Surface form Disambiguated ID Type / Status
Subject Cagayan E298919 entity
Predicate hasCity P316 FINISHED
Object Gattaran
Gattaran is a municipality in the province of Cagayan in the Cagayan Valley region of the Philippines, known for its agricultural lands and proximity to the Cagayan River.
 E986697 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: Gattaran | Statement: [Cagayan, hasCity, Gattaran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gattaran
Context triple: [Cagayan, hasCity, Gattaran]
  • A. Gutu
    Gutu is a town and district in southeastern Zimbabwe known for its rural communities and agricultural activities within Masvingo Province.
  • B. Galang
    Galang is an island in Indonesia’s Riau Islands province, historically known for hosting a Vietnamese refugee camp during the late 20th century.
  • C. Sagala
    Sagala was an important ancient city in the Punjab region, historically known as a major political and cultural center under Indo-Greek rule.
  • D. Galibi
    Galibi is a coastal village in northeastern Suriname known for its indigenous communities and important sea turtle nesting beaches.
  • E. Goura
    Goura is a small village in the Peloponnese region of Greece, known for its traditional stone architecture and mountainous surroundings.
  • 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: Gattaran
Triple: [Cagayan, hasCity, Gattaran]
Generated description
Gattaran is a municipality in the province of Cagayan in the Cagayan Valley region of the Philippines, known for its agricultural lands and proximity to the Cagayan River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gattaran
Target entity description: Gattaran is a municipality in the province of Cagayan in the Cagayan Valley region of the Philippines, known for its agricultural lands and proximity to the Cagayan River.
  • A. Gutu
    Gutu is a town and district in southeastern Zimbabwe known for its rural communities and agricultural activities within Masvingo Province.
  • B. Galang
    Galang is an island in Indonesia’s Riau Islands province, historically known for hosting a Vietnamese refugee camp during the late 20th century.
  • C. Sagala
    Sagala was an important ancient city in the Punjab region, historically known as a major political and cultural center under Indo-Greek rule.
  • D. Galibi
    Galibi is a coastal village in northeastern Suriname known for its indigenous communities and important sea turtle nesting beaches.
  • E. Goura
    Goura is a small village in the Peloponnese region of Greece, known for its traditional stone architecture and mountainous surroundings.
  • 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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dfddf38819099263b8b1e804736 completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bb5af708190b3786da334c3bf23 completed May 2, 2026, 7:08 p.m.
NEDg Description generation batch_69f64ce1b0ec8190bcbd245255e548b5 completed May 2, 2026, 7:13 p.m.
NED2 Entity disambiguation (via description) batch_69f64da735f48190b051ce173c13e5b2 completed May 2, 2026, 7:16 p.m.
Created at: April 8, 2026, 9:57 p.m.