Triple

T14995914
Position Surface form Disambiguated ID Type / Status
Subject Province of Palermo (historical) E373957 entity
Predicate contains P35 FINISHED
Object Cinisi E269087 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: Cinisi | Statement: [Province of Palermo (historical), contains, Cinisi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cinisi
Context triple: [Province of Palermo (historical), contains, Cinisi]
  • A. Cinisi chosen
    Cinisi is a coastal town in the Metropolitan City of Palermo in Sicily, Italy, known for its proximity to Palermo’s main international airport.
  • B. Carovigno
    Carovigno is a historic town and popular tourist destination in Italy’s Apulia region, known for its medieval castle, olive groves, and proximity to the Adriatic coast.
  • C. Rissani
    Rissani is a historic town in eastern Morocco, known as a gateway to the Sahara Desert and an important former caravan and trading center.
  • D. Quarracino
    Quarracino is an Italian-origin surname most notably associated with Argentine Cardinal Antonio Quarracino.
  • E. Casarico
    Casarico is a locality or hamlet that forms part of the municipality of Moltrasio in the Lombardy region of northern Italy.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded718e4288190b5e144f82299a194 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe969a63f081908bf11783e2a51229 completed May 9, 2026, 2:06 a.m.
Created at: April 10, 2026, 2:53 a.m.