Triple

T441618
Position Surface form Disambiguated ID Type / Status
Subject Quezon City E10123 entity
Predicate hasSisterCity P919 FINISHED
Object Naga
Naga is a city in the Bicol Region of the Philippines known as a major religious, cultural, and commercial center, particularly famed for the annual Peñafrancia Festival.
 E65234 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: Naga | Statement: [Quezon City, hasSisterCity, Naga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Naga
Context triple: [Quezon City, hasSisterCity, Naga]
  • A. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • B. Ranna
    Ranna was a prominent 10th-century Kannada poet, celebrated as one of the “three gems” of early Kannada literature for his influential epic and courtly works.
  • C. Nain
    Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
  • D. Rana
    Rana was the hereditary royal title borne by the ruling dynasty of the former princely state of Porbandar in western India.
  • E. Yama
    Yama is the Hindu god of death and justice, traditionally regarded as the ruler of the afterlife and judge of the souls of the dead.
  • 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: Naga
Triple: [Quezon City, hasSisterCity, Naga]
Generated description
Naga is a city in the Bicol Region of the Philippines known as a major religious, cultural, and commercial center, particularly famed for the annual Peñafrancia Festival.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Naga
Target entity description: Naga is a city in the Bicol Region of the Philippines known as a major religious, cultural, and commercial center, particularly famed for the annual Peñafrancia Festival.
  • A. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • B. Ranna
    Ranna was a prominent 10th-century Kannada poet, celebrated as one of the “three gems” of early Kannada literature for his influential epic and courtly works.
  • C. Nain
    Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
  • D. Rana
    Rana was the hereditary royal title borne by the ruling dynasty of the former princely state of Porbandar in western India.
  • E. Yama
    Yama is the Hindu god of death and justice, traditionally regarded as the ruler of the afterlife and judge of the souls of the dead.
  • 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_69a2e8465ef481909655c681b01e2986 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2ef42b4008190abed9d79926c7022 completed Feb. 28, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ab1982f48190b7d7300f0ab9c637 completed March 1, 2026, 9:09 p.m.
NEDg Description generation batch_69a4ac032ef4819094b9ce7740262eda completed March 1, 2026, 9:13 p.m.
NED2 Entity disambiguation (via description) batch_69a4ada4ca5481909bbd62b55f10f4f9 completed March 1, 2026, 9:20 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.