Triple
T9857880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A109BA |
E239633
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Agusta |
E313895
|
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: Agusta | Statement: [A109BA, manufacturer, Agusta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agusta Context triple: [A109BA, manufacturer, Agusta]
-
A.
Agusta
chosen
Agusta is an Italian aerospace company known for manufacturing helicopters and aircraft, often under license from other major aviation firms.
-
B.
AnsaldoBreda
AnsaldoBreda is an Italian rolling stock manufacturer known for producing trains, trams, and metro vehicles for rail systems worldwide.
-
C.
SIAI-Marchetti
SIAI-Marchetti was an Italian aircraft manufacturer known for producing light military trainers and aerobatic aircraft.
-
D.
Piaggio
Piaggio is an Italian manufacturer best known for producing scooters, motorcycles, and light commercial vehicles, including the iconic Vespa.
-
E.
Caproni
Caproni was an Italian aircraft manufacturer renowned for producing military and civilian airplanes, particularly during the early to mid-20th century.
- 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_69ca84e6493081909cf58c8d42ea856b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb399bd8081908281d1735cc3909f |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e43b2de881909e00f6701d1c7b54 |
completed | April 5, 2026, 4:25 a.m. |
Created at: March 30, 2026, 8:35 p.m.