Triple

T1711562
Position Surface form Disambiguated ID Type / Status
Subject Düsseldorf E36993 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: [Düsseldorf, twinCity, Palermo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palermo
Context triple: [Düsseldorf, twinCity, Palermo]
  • A. Palermo
    Palermo is a large, upscale neighborhood in Buenos Aires known for its parks, nightlife, cultural attractions, and trendy dining and shopping areas.
  • B. 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.
  • 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. Messina
    Messina is a major port city in northeastern Sicily, Italy, located on the Strait of Messina opposite mainland Calabria.
  • E. Catania
    Catania is a historic port city on the eastern coast of Sicily, Italy, known for its Baroque architecture and proximity to Mount Etna.
  • 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_69a88617439c819094ffb5d16a0f6307 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6315afdc81908409435bb47e8ee0 completed March 6, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae303cdce081909b66ec04de43cf53 completed March 9, 2026, 2:28 a.m.
Created at: March 4, 2026, 7:30 p.m.