Triple
T14785760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avio S.p.A. |
E347518
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object | Colleferro |
E1138618
|
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: Colleferro | Statement: [Avio S.p.A., headquartersLocation, Colleferro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colleferro Context triple: [Avio S.p.A., headquartersLocation, Colleferro]
-
A.
Colleferro
chosen
Colleferro is an industrial town in the Lazio region of central Italy, known for its manufacturing and aerospace industries.
-
B.
Vetralla
Vetralla is a historic town and comune in the Lazio region of central Italy, known for its medieval architecture and location along the ancient Via Cassia.
-
C.
Montecastrilli
Montecastrilli is a small Italian municipality in the Umbria region, known for its rural landscapes and historic hilltop setting.
-
D.
Montefiascone
Montefiascone is a historic hilltop town in Italy’s Lazio region, known for its scenic views over Lake Bolsena and its production of the Est! Est!! Est!!! white wine.
-
E.
Roccaraso
Roccaraso is a mountain town in Italy’s Abruzzo region, renowned as one of the country’s major ski and winter sports resorts.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decaa083e481908336d58d026eec32 |
completed | April 14, 2026, 11:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5dee8988190b80cb487c12bfc2d |
completed | May 9, 2026, 7:44 a.m. |
Created at: April 10, 2026, 1:31 a.m.