Triple
T14991169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ArgoNeuT |
E373837
|
entity |
| Predicate | hasActiveVolume |
P20330
|
FINISHED |
| Object | approximately 170 liters |
—
|
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: approximately 170 liters | Statement: [ArgoNeuT, hasActiveVolume, approximately 170 liters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasActiveVolume Context triple: [ArgoNeuT, hasActiveVolume, approximately 170 liters]
-
A.
hasExposedVolume
Indicates that a volume or space is open or exposed to its surroundings rather than fully enclosed or covered.
-
B.
hasActiveNucleus
Indicates that the referenced entity possesses a nucleus that is currently functioning or exhibiting biological activity.
-
C.
supportsVolumeControl
Indicates that one entity provides the capability to adjust or manage the audio volume level of another entity.
-
D.
hasVolumeDescriptor
chosen
Indicates that something is associated with a qualitative or quantitative description of its volume.
-
E.
hasLargeVolume
Indicates that an entity possesses or is characterized by a comparatively large physical or quantitative volume.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded715db408190b44e8a8452c79764 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:53 a.m.