Triple
T15839343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BeppoSAX |
E384060
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Alenia Spazio |
E718375
|
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: Alenia Spazio | Statement: [BeppoSAX, manufacturer, Alenia Spazio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alenia Spazio Context triple: [BeppoSAX, manufacturer, Alenia Spazio]
-
A.
Alenia Spazio
chosen
Alenia Spazio is an Italian aerospace company specializing in the design and manufacture of space systems, satellites, and modules for international space programs.
-
B.
Alenia Aeronautica
Alenia Aeronautica was an Italian aerospace company known for designing and producing military and civilian aircraft before being merged into Leonardo’s aeronautics division.
-
C.
Avio S.p.A.
Avio S.p.A. is an Italian aerospace company specializing in the design, production, and maintenance of aircraft and space propulsion systems.
-
D.
Telespazio
Telespazio is a major European space services company specializing in satellite operations, telecommunications, Earth observation, and navigation solutions.
-
E.
AnsaldoBreda
AnsaldoBreda is an Italian rolling stock manufacturer known for producing trains, trams, and metro vehicles for rail systems worldwide.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e4fa24819086a1a226082ac2d3 |
completed | April 16, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa13c931481908ed9fd10fddd867c |
completed | May 9, 2026, 9:03 p.m. |
Created at: April 10, 2026, 4:49 a.m.