Triple
T2179461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ERC Consolidator Grant |
E49005
|
entity |
| Predicate | maximumGrantAmount |
P37671
|
FINISHED |
| Object | up to 2 million euro |
—
|
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: up to 2 million euro | Statement: [ERC Consolidator Grant, maximumGrantAmount, up to 2 million euro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumGrantAmount Context triple: [ERC Consolidator Grant, maximumGrantAmount, up to 2 million euro]
-
A.
maximumLoanAmountUSD
Indicates the highest amount of money, expressed in U.S. dollars, that can be loaned under a given agreement or condition.
-
B.
loanLimitType
Indicates the category or rule that defines how a loan’s maximum allowable amount or terms are limited.
-
C.
awardAmount
Indicates the specific quantity or value of an award that is granted in the context of a particular awarding event or relationship.
-
D.
typicalAwardAmount
Indicates the usual or most common amount of an award given in this relationship.
-
E.
hasMonetaryGrant
Indicates that an entity provides or receives a monetary grant from another entity.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abc434978c8190b9c4dd8411b87f23 |
completed | March 7, 2026, 6:22 a.m. |
Created at: March 4, 2026, 7:45 p.m.