Triple
T11962476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CAF UK |
E284701
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | CAF Group |
E956945
|
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: CAF Group | Statement: [CAF UK, partOf, CAF Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAF Group Context triple: [CAF UK, partOf, CAF Group]
-
A.
CAF Group
chosen
CAF Group is a multinational Spanish company specializing in the design, manufacture, and maintenance of railway vehicles and related transport systems.
-
B.
ACP Group
The ACP Group is an intergovernmental organization of African, Caribbean, and Pacific states that primarily collaborates with the European Union on development cooperation and trade.
-
C.
ACS Group
ACS Group is a major Spanish multinational construction and civil engineering company known for its global infrastructure projects and ownership of several large contractors.
-
D.
ANA Group
ANA Group is a major Japanese aviation conglomerate centered around All Nippon Airways, operating passenger and cargo airlines as well as related aviation services.
-
E.
CJ Group
CJ Group is a major South Korean conglomerate with diversified businesses spanning entertainment, media, food, biotechnology, and retail.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037848f481908276716675464464 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f471d625c88190baed4ea08853988a |
completed | May 1, 2026, 9:26 a.m. |
Created at: April 8, 2026, 9:45 p.m.