Triple

T13875180
Position Surface form Disambiguated ID Type / Status
Subject A25 motorway E333562 entity
Predicate connectsTo P845 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: [A25 motorway, connectsTo, Pescara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pescara
Context triple: [A25 motorway, connectsTo, 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0be556708190bbcf0b3583f677e3 completed April 14, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe967cea3c81909d9b600501897a41 completed May 9, 2026, 2:05 a.m.
Created at: April 9, 2026, 10:15 p.m.