Triple
T1798230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centauro tank destroyer |
E39653
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object |
Iveco
Iveco is an Italian multinational company that designs and manufactures commercial vehicles, military vehicles, and diesel engines.
|
E200926
|
NE FINISHED |
How this triple was built (4 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: Iveco | Statement: [Centauro tank destroyer, manufacturer, Iveco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iveco Context triple: [Centauro tank destroyer, manufacturer, Iveco]
-
A.
Fiat
Fiat is an Italian automobile manufacturer known for producing compact city cars and mass-market vehicles, now operating as a brand within the multinational automotive group Stellantis.
-
B.
Fiat Ducato
The Fiat Ducato is a popular light commercial van produced by Fiat, widely used across Europe for cargo transport, camper conversions, and other utility purposes.
-
C.
Hino
Hino is a town in Shiga Prefecture, Japan, known for its historical streetscapes and traditional industries.
-
D.
Hino
Hino is a city in western Tokyo, Japan, known as a residential and industrial suburb within the Tama area.
-
E.
Scania
Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Iveco Triple: [Centauro tank destroyer, manufacturer, Iveco]
Generated description
Iveco is an Italian multinational company that designs and manufactures commercial vehicles, military vehicles, and diesel engines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Iveco Target entity description: Iveco is an Italian multinational company that designs and manufactures commercial vehicles, military vehicles, and diesel engines.
-
A.
Fiat
Fiat is an Italian automobile manufacturer known for producing compact city cars and mass-market vehicles, now operating as a brand within the multinational automotive group Stellantis.
-
B.
Fiat Ducato
The Fiat Ducato is a popular light commercial van produced by Fiat, widely used across Europe for cargo transport, camper conversions, and other utility purposes.
-
C.
Hino
Hino is a town in Shiga Prefecture, Japan, known for its historical streetscapes and traditional industries.
-
D.
Hino
Hino is a city in western Tokyo, Japan, known as a residential and industrial suburb within the Tama area.
-
E.
Scania
Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
- F. None of above. chosen
Provenance (5 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_69a88632aa588190ba3978fde0db5bbd |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa6568373c81908044e0cd8a38344d |
completed | March 6, 2026, 5:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5d8da888190a88f3bd8036e19f4 |
completed | March 8, 2026, 5:46 p.m. |
| NEDg | Description generation | batch_69adb69c149081908b5b819c068a1ce2 |
completed | March 8, 2026, 5:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb8be528c819092a5e22b099fc2a0 |
completed | March 8, 2026, 5:58 p.m. |
Created at: March 4, 2026, 7:32 p.m.