Triple
T8936381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Type 10 Light Rail Vehicle |
E212786
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | CAF USA |
E59649
|
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 USA | Statement: [Type 10 Light Rail Vehicle, manufacturer, CAF USA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAF USA Context triple: [Type 10 Light Rail Vehicle, manufacturer, CAF USA]
-
A.
CAF
CAF is the commonly used acronym for the Canadian Armed Forces, the unified military organization responsible for defending Canada and supporting international peace and security operations.
-
B.
CAF
CAF is an abbreviation that can refer to various organizations or groups, most notably the Cactus Air Force, a World War II Allied air unit based on Guadalcanal.
-
C.
CAF
CAF is a multilateral development bank that finances sustainable development and regional integration projects across Latin America and the Caribbean.
-
D.
CAF
CAF is the acronym for "Comando de Apoyo a la Fuerza," a military support command unit within the Spanish Armed Forces.
-
E.
CAF
chosen
CAF is a Spanish multinational company that designs and manufactures railway vehicles and related transport equipment used by metro 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_69ca839694c88190b324ffeb43d23b08 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66928cec8190915636d663f843af |
completed | April 1, 2026, 12:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc937ded08190a67fd4457b6458ff |
completed | April 3, 2026, 2:05 p.m. |
Created at: March 30, 2026, 6:58 p.m.