Triple
T14773283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ACL2 |
E347188
|
entity |
| Predicate | evaluationModel |
P115738
|
FINISHED |
| Object | applicative (functional) programming model |
—
|
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: applicative (functional) programming model | Statement: [ACL2, evaluationModel, applicative (functional) programming model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: evaluationModel Context triple: [ACL2, evaluationModel, applicative (functional) programming model]
-
A.
evaluationAspect
Indicates the specific dimension or criterion of performance or quality that is being assessed within an evaluation.
-
B.
evaluationBasis
Indicates the criteria, standards, or reference framework used to judge, assess, or measure something in an evaluation process.
-
C.
evaluationRole
Indicates the role or capacity in which an entity participates in an evaluation or assessment process.
-
D.
evaluationFunction
Indicates a relationship where a specific procedure or rule assigns a value or score to an input, typically to assess its quality, utility, or desirability.
-
E.
evaluationUse
Indicates that something is used as a basis, tool, or resource for evaluating or assessing something else.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec81485e08190be35baafcf22b6f2 |
completed | April 14, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69de8c02e5c08190943c27594026faf7 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:31 a.m.