Triple
T11096947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Globalisation Adjustment Fund |
E262400
|
entity |
| Predicate | maximumEUcofinancingRate |
P97218
|
FINISHED |
| Object | 60% |
—
|
LITERAL 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: 60% | Statement: [European Globalisation Adjustment Fund, maximumEUcofinancingRate, 60%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumEUcofinancingRate Context triple: [European Globalisation Adjustment Fund, maximumEUcofinancingRate, 60%]
-
A.
maximumGrantAmount
Indicates the highest monetary value that can be awarded or granted under a specific grant, program, or agreement.
-
B.
fundingCapType
Indicates the classification or category of a limit placed on the amount of funding that can be provided.
-
C.
federalMatchRate
Indicates the proportion of costs or funding that is covered or matched by the federal government relative to non-federal contributions.
-
D.
euroParticipation
Indicates that an entity takes part in or is involved with the Euro currency system or Eurozone monetary framework.
-
E.
maximumLoanAmountUSD
Indicates the highest amount of money, expressed in U.S. dollars, that can be loaned under a given agreement or condition.
- F. None of above. chosen
Provenance (4 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a0a02cc8190a15df663d4860163 |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d7441aa3548190b92dbde57841c135 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750ca52ec8190a559432a5de106fd |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:27 p.m.