Triple
T2319179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gorely |
E51136
|
entity |
| Predicate | gasEmissions |
P22265
|
FINISHED |
| Object | sulfur-rich fumarolic gases |
—
|
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: sulfur-rich fumarolic gases | Statement: [Gorely, gasEmissions, sulfur-rich fumarolic gases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gasEmissions Context triple: [Gorely, gasEmissions, sulfur-rich fumarolic gases]
-
A.
emissionsControl
Indicates a relationship where one entity regulates, limits, or manages the release of emissions produced by another entity or process.
-
B.
fuelEfficiency
Indicates how effectively an entity uses fuel to perform a given amount of work or travel a certain distance.
-
C.
gasContent
chosen
Indicates that one entity has, contains, or is characterized by a certain amount or type of gas.
-
D.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
E.
carbonDioxideLevel
Indicates the measured concentration or amount of carbon dioxide present in a given environment or system.
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.