Triple

T7544567
Position Surface form Disambiguated ID Type / Status
Subject Montpellier E178364 entity
Predicate twinCity P1072 FINISHED
Object Palermo E76466 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: [Montpellier, twinCity, Palermo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palermo
Context triple: [Montpellier, twinCity, Palermo]
  • A. Palermo
    Palermo is a 90 nm, low-power, budget-oriented core used in AMD's Sempron line of processors.
  • B. Palermo
    Palermo is a large, upscale neighborhood in Buenos Aires known for its parks, nightlife, cultural attractions, and trendy dining and shopping areas.
  • C. Palermo chosen
    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.
  • D. Palermo
    Palermo is a municipality in the Huila Department of southern Colombia, known for its agricultural activities and proximity to the departmental capital, Neiva.
  • 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_69c69f2be3888190a6667a27f8f195e9 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f898069881909fa8f9c885c4565b completed March 27, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8614c958081908021a0341dc29725 completed March 28, 2026, 11:16 p.m.
Created at: March 27, 2026, 3:48 p.m.