Triple
T14911449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ortona |
E371270
|
entity |
| Predicate | near |
P350
|
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: [Ortona, near, Pescara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pescara Context triple: [Ortona, near, 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded61d75008190b6f9a1a38137836f |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a1d8e088190a2168952ab5dc687 |
completed | May 10, 2026, 1:37 p.m. |
Created at: April 10, 2026, 2:26 a.m.