Triple
T3008551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wildlife and Sport Fish Restoration Program |
E81959
|
entity |
| Predicate | allocationCriterion |
P37407
|
FINISHED |
| Object | land area |
—
|
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: land area | Statement: [Wildlife and Sport Fish Restoration Program, allocationCriterion, land area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allocationCriterion Context triple: [Wildlife and Sport Fish Restoration Program, allocationCriterion, land area]
-
A.
selectionCriteria
Indicates the conditions or rules used to choose certain entities from a larger set.
-
B.
selectionMetric
Indicates the criterion or measure used to evaluate and choose among alternative options or candidates.
-
C.
evaluationCriteriaInclude
Indicates that certain criteria are part of, or explicitly included in, the set of standards used to evaluate something.
-
D.
awardCriteria
Indicates the standards or conditions used to determine eligibility for receiving an award or recognition.
-
E.
allocatesAccordingTo
chosen
Indicates that one entity distributes or assigns resources, tasks, or responsibilities to others based on a specified rule, criterion, or plan.
- F. None of above.
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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a4ba6988190be29c00cd4266941 |
completed | March 8, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69ad96180eb08190a524c5f458d41382 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.