Triple

T11603287
Position Surface form Disambiguated ID Type / Status
Subject Qormi E275185 entity
Predicate hasTwinTown P919 FINISHED
Object Pescara E32082 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: Pescara | Statement: [Qormi, hasTwinTown, Pescara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pescara
Context triple: [Qormi, hasTwinTown, Pescara]
  • A. Pescara chosen
    Pescara is a coastal city in the Abruzzo region of central Italy, known for its Adriatic beaches, modern urban layout, and role as a commercial and tourist hub.
  • B. Chieti
    Chieti is an ancient city in the Abruzzo region of central Italy, known for its Roman archaeological sites and medieval architecture.
  • C. Ancona
    Ancona is a historic port city on Italy’s Adriatic coast, notable for its long-standing Jewish community and role as a commercial and cultural crossroads.
  • D. Foggia
    Foggia is a city in the Apulia region of southern Italy, historically significant as a medieval center and later as an important agricultural and commercial hub.
  • E. Lecce
    Lecce is a historic city in Italy’s Apulia region, renowned for its rich Baroque architecture and cultural heritage.
  • 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_69d6aaf84b548190ac072e4fb89ae18f completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8954daa908190a8d532e43aa4a881 completed April 10, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69f61e33557c8190a724bb45c59abc63 completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:38 p.m.