Triple

T13826907
Position Surface form Disambiguated ID Type / Status
Subject A14 motorway E332273 entity
Predicate passesThrough P225 FINISHED
Object Chieti E208665 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: Chieti | Statement: [A14 motorway, passesThrough, Chieti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chieti
Context triple: [A14 motorway, passesThrough, Chieti]
  • A. Chieti chosen
    Chieti is an ancient city in the Abruzzo region of central Italy, known for its Roman archaeological sites and medieval architecture.
  • B. Pescara
    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.
  • C. Teramo
    Teramo is a historic city in the Abruzzo region of central Italy, known for its Roman archaeological remains and medieval architecture.
  • D. Terni
    Terni is an industrial city in the Umbria region of central Italy, known for its steel production and historic Roman and medieval heritage.
  • E. 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.
  • 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_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0295d2d48190b08eba0d805bd72d completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe64e47f1c8190a4ad09bc96d35b69 completed May 8, 2026, 10:34 p.m.
Created at: April 9, 2026, 10:13 p.m.