Triple
T316228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgian traditional Qvevri wine-making |
E7712
|
entity |
| Predicate | vesselLocationDuringUse |
P11946
|
FINISHED |
| Object | buried underground |
—
|
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: buried underground | Statement: [Georgian traditional Qvevri wine-making, vesselLocationDuringUse, buried underground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vesselLocationDuringUse Context triple: [Georgian traditional Qvevri wine-making, vesselLocationDuringUse, buried underground]
-
A.
usesAtSea
Indicates that something is employed, operated, or applied in a maritime or oceanic environment.
-
B.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
-
C.
usedInMaritimeNavigation
Indicates that something is employed as a tool, aid, or reference in the practice of maritime navigation.
-
D.
maritimeUsage
Indicates the extent to which something is used for or involved in maritime activities, such as sea transport, navigation, or ocean-related operations.
-
E.
cabinLocation
Indicates the spatial or geographic location associated with a cabin.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea6462148190825acc57f6d2adaf |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e943f12c8190883854aeed974260 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea08878c8190a5e8a90f620a3888 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.