Triple

T8541706
Position Surface form Disambiguated ID Type / Status
Subject Amazon region of Ecuador E202212 entity
Predicate hasMajorCity P316 FINISHED
Object Puyo E247429 NE FINISHED

How this triple was built (2 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: Puyo | Statement: [Amazon region of Ecuador, hasMajorCity, Puyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Puyo
Context triple: [Amazon region of Ecuador, hasMajorCity, Puyo]
  • A. Puyo chosen
    Puyo is a small city in eastern Ecuador that serves as a gateway to the Amazon rainforest and a regional center for eco-tourism and trade.
  • B. Puyo Puyo
    Puyo Puyo is a fast-paced puzzle video game series by Sega, known for its colorful blob characters and competitive chain-combo gameplay.
  • C. Piku
    Piku is a 2015 Indian comedy-drama film centered on the relationship between a headstrong daughter and her aging, hypochondriac father, featuring a notable performance by Amitabh Bachchan.
  • D. Pengo
    Pengo is a Dravidian language spoken primarily by the Pengo people in parts of central India, especially in Odisha and neighboring regions.
  • E. Pallette
    Pallette is a surname most notably associated with American character actor Eugene Pallette, known for his distinctive gravelly voice and roles in classic Hollywood films of the 1930s and 1940s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca832461e88190a654c5e44e233aa8 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6e10bc081909a7210c577b807fb completed March 31, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6da3d65c819087ed6b46dfc35885 completed April 2, 2026, 1:22 p.m.
Created at: March 30, 2026, 6:18 p.m.