Triple

T16195479
Position Surface form Disambiguated ID Type / Status
Subject Lasithi Plateau E393049 entity
Predicate hasSettlement P1068 FINISHED
Object Pinakiano E1198692 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: Pinakiano | Statement: [Lasithi Plateau, hasSettlement, Pinakiano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pinakiano
Context triple: [Lasithi Plateau, hasSettlement, Pinakiano]
  • A. Pinakiano chosen
    Pinakiano is a small village located on the Lasithi Plateau in eastern Crete, Greece, within the Oropedio Lasithiou municipality.
  • B. Pilcaniyeu
    Pilcaniyeu is a small town in Argentina’s Patagonia region, located in the Andean area of Río Negro Province and known for its rural character and nearby natural landscapes.
  • C. Punakapina
    Punakapina is the Finnish Civil War of 1918, a conflict between the socialist Reds and conservative Whites that shaped Finland’s early independence.
  • D. Palawano
    Palawano is an Austronesian language spoken by the indigenous Palawano people of Palawan in the Philippines.
  • E. Mabini
    Mabini is a coastal municipality in the province of Batangas in the Philippines, known for its diving spots and marine biodiversity.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222d91130819080da4e2611612e27 completed April 17, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00078bbc388190b3fb793556ddd75a completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5:02 a.m.