Triple
T18318042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1 Billion Meals initiative |
E438797
|
entity |
| Predicate | measuresImpactIn |
P131319
|
FINISHED |
| Object | number of meals distributed |
—
|
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: number of meals distributed | Statement: [1 Billion Meals initiative, measuresImpactIn, number of meals distributed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: measuresImpactIn Context triple: [1 Billion Meals initiative, measuresImpactIn, number of meals distributed]
-
A.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
B.
measuredEffect
Indicates that an action or process has produced a specific, quantified outcome or impact on something.
-
C.
examinesImpactOn
Indicates that one entity studies, evaluates, or analyzes the effects or consequences that another entity has on a specified subject or outcome.
-
D.
hasImpactScale
Indicates the degree or magnitude of impact that one entity or action has on another, typically expressed along a defined scale.
-
E.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aa342a881909afcd995405027af |
completed | April 19, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69e44fe4ee10819086b4142444fca1f5 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:36 a.m.