Triple
T11078852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hubble Space Telescope solar arrays |
E261934
|
entity |
| Predicate | environmentalExposure |
P77335
|
FINISHED |
| Object | vacuum |
—
|
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: vacuum | Statement: [Hubble Space Telescope solar arrays, environmentalExposure, vacuum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: environmentalExposure Context triple: [Hubble Space Telescope solar arrays, environmentalExposure, vacuum]
-
A.
routeOfExposure
Indicates the pathway or method by which an agent, substance, or factor comes into contact with or enters an organism or system.
-
B.
environmentalFactor
chosen
Indicates that one entity functions as an environmental influence or condition that affects another entity or process.
-
C.
hasEnvironmentalRisk
Indicates that an entity poses, contributes to, or is associated with potential harm or adverse impact on the environment.
-
D.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
E.
hasEnvironmentalImpactType
Indicates that something affects the environment in a specific way categorized by a particular type of impact.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799953d58819096b645a1377e70f2 |
completed | April 9, 2026, 12:20 p.m. |
| PD | Predicate disambiguation | batch_69d74415403c81909778bcd829e8832e |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.