Triple
T6164512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | welfare economics |
E137522
|
entity |
| Predicate | appliesCriterion |
P50251
|
FINISHED |
| Object | efficiency |
—
|
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: efficiency | Statement: [welfare economics, appliesCriterion, efficiency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesCriterion Context triple: [welfare economics, appliesCriterion, efficiency]
-
A.
hasQualityCriterion
chosen
Indicates that something is associated with a specific standard or criterion used to judge its quality.
-
B.
appliesIf
Indicates that a rule, condition, or operation is applicable only when certain specified criteria or circumstances are met.
-
C.
hasCriterionType
Indicates that something is associated with or classified by a specific type of criterion used for evaluation or decision-making.
-
D.
appliesFrom
Indicates that a rule, condition, or effect begins to be applicable starting from a specific point in time or state.
-
E.
selectionCriteria
Indicates the conditions or rules used to choose certain entities from a larger set.
- 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_69c008a54fc88190b6ce4416490ca79d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d6036f88190a4bf540e7fe8d48d |
completed | March 22, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69c055f5b81481908819515cdc334ae6 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:17 p.m.