Triple

T10931335
Position Surface form Disambiguated ID Type / Status
Subject Las Cañitas E258213 entity
Predicate partOf P40 FINISHED
Object Palermo E50157 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: Palermo | Statement: [Las Cañitas, partOf, Palermo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palermo
Context triple: [Las Cañitas, partOf, Palermo]
  • A. Palermo chosen
    Palermo is a large, upscale neighborhood in Buenos Aires known for its parks, nightlife, cultural attractions, and trendy dining and shopping areas.
  • B. Palermo
    Palermo is the historic capital of Sicily, renowned for its rich multicultural heritage, including a significant medieval Jewish presence, and its blend of Arab-Norman architecture, vibrant markets, and coastal setting.
  • C. Palermo
    Palermo is a municipality in the Huila Department of southern Colombia, known for its agricultural activities and proximity to the departmental capital, Neiva.
  • D. Palermo
    Palermo is a 90 nm, low-power, budget-oriented core used in AMD's Sempron line of processors.
  • E. Messina
    Messina is a major port city in northeastern Sicily, Italy, located on the Strait of Messina opposite mainland Calabria.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770a062f481908beb76c6dbaeb6a6 completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2162f1f648190b325c7e7647b543e completed April 17, 2026, 11:14 a.m.
Created at: April 8, 2026, 9:23 p.m.