Triple

T4058666
Position Surface form Disambiguated ID Type / Status
Subject Tarlac E84755 entity
Predicate hasCity P316 FINISHED
Object Victoria
Victoria is a municipality in the province of Tarlac in the Central Luzon region of the Philippines.
E411889 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: Victoria | Statement: [Tarlac, hasCity, Victoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victoria
Context triple: [Tarlac, hasCity, Victoria]
  • A. Victoria
    Victoria is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and agricultural economy.
  • B. Victoria
    Victoria is a vengeful vampire antagonist from the Twilight series who relentlessly hunts Bella Swan and opposes the Cullen family.
  • C. Victoria
    Victoria is a southeastern Australian state known for its capital city Melbourne, cultural diversity, and varied landscapes ranging from coastal regions to alpine areas.
  • D. Victoria
    Victoria was the Spanish carrack that became the first ship to successfully circumnavigate the globe during Ferdinand Magellan’s expedition.
  • E. Victoria
    Victoria is a feminine given name of Latin origin meaning "victory," borne by numerous notable figures including queens, saints, and public personalities.
  • 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: Victoria
Triple: [Tarlac, hasCity, Victoria]
Generated description
Victoria is a municipality in the province of Tarlac in the Central Luzon region of the Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Victoria
Target entity description: Victoria is a municipality in the province of Tarlac in the Central Luzon region of the Philippines.
  • A. Victoria
    Victoria is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and agricultural economy.
  • B. Victoria
    Victoria is a municipality and town located in the Caldas Department of central Colombia.
  • C. Victoria
    Victoria is a major city in southeastern Australia and the capital of the state of Victoria, known for its rich cultural scene, historic architecture, and status as a key economic and population center.
  • D. Victoria
    Victoria is a southeastern Australian state known for its capital city Melbourne, cultural diversity, and varied landscapes ranging from coastal regions to alpine areas.
  • E. Victoria
    Victoria is a coastal city on the southern tip of Vancouver Island known for its historic architecture, mild climate, and vibrant tourism industry.
  • 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbd13b4481908f9c09cc4f4a9724 completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562a6250081908f289f43b066b04d completed March 14, 2026, 1:29 p.m.
NEDg Description generation batch_69b563b3db0481909f3dd2a9e6a88e6e completed March 14, 2026, 1:33 p.m.
NED2 Entity disambiguation (via description) batch_69b567e223cc8190aa1d7e827e6c70fd completed March 14, 2026, 1:51 p.m.
Created at: March 9, 2026, 3:38 p.m.