Triple

T1324716
Position Surface form Disambiguated ID Type / Status
Subject Prince of Canino and Musignano E28299 entity
Predicate associatedTerritory P1103 FINISHED
Object Canino E43163 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: Canino | Statement: [Prince of Canino and Musignano, associatedTerritory, Canino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canino
Context triple: [Prince of Canino and Musignano, associatedTerritory, Canino]
  • A. Canino chosen
    Canino is a small town in the Lazio region of central Italy, historically notable as the birthplace of Pope Paul III.
  • B. San Bernardo
    San Bernardo is a commune and city in Chile that forms part of the Greater Santiago urban area and serves as an important residential and industrial hub.
  • C. Dongo
    Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
  • D. Cáqueza
    Cáqueza is a small municipality and town in the Andean region of central Colombia, known for its rural landscapes and proximity to Bogotá in the department of Cundinamarca.
  • E. Pekela
    Pekela is a municipality in the province of Groningen in the northeastern Netherlands, known for its rural character and historical peat colonies.
  • 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_69a498540a2481909e807a762280d3ba completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c19e81c0819092f85201ae34422a completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf2e13dc8190902879be5fa69adb completed March 8, 2026, 12:13 a.m.
Created at: March 1, 2026, 7:55 p.m.