Triple
T4052459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asahi Glass Foundation |
E84614
|
entity |
| Predicate | BluePlanetPrizeCategory |
P53011
|
FINISHED |
| Object | environmental science |
—
|
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: environmental science | Statement: [Asahi Glass Foundation, BluePlanetPrizeCategory, environmental science]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BluePlanetPrizeCategory Context triple: [Asahi Glass Foundation, BluePlanetPrizeCategory, environmental science]
-
A.
marineLifeTrend
Indicates a change over time in the abundance, health, or distribution of marine life populations.
-
B.
hasMarineSpecies
Indicates that an entity contains, supports, or is associated with one or more marine species.
-
C.
primaryMarineSpeciesObserved
Indicates that the specified marine species is the main or most frequently observed species in a given observation or survey context.
-
D.
hasMarineEcosystem
Indicates that an entity possesses, contains, or is associated with a marine ecosystem as part of its characteristics or environment.
-
E.
eraClassification
Indicates the historical era or time period into which an entity is categorized or classified.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb869c34819097ec3bebe402d37b |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef90249e4819095e9e043bc4aa9a6 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef9fcb31c819098d5287b6fc84f4e |
completed | March 9, 2026, 4:49 p.m. |
Created at: March 9, 2026, 3:37 p.m.