Triple
T316253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgian traditional Qvevri wine-making |
E7712
|
entity |
| Predicate | involvesCraft |
P5963
|
FINISHED |
| Object | qvevri pottery making |
—
|
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: qvevri pottery making | Statement: [Georgian traditional Qvevri wine-making, involvesCraft, qvevri pottery making]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesCraft Context triple: [Georgian traditional Qvevri wine-making, involvesCraft, qvevri pottery making]
-
A.
traditionalCraft
chosen
Indicates that an entity is associated with or practices a craft or skill that is rooted in long-established, culturally transmitted traditions.
-
B.
involves
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
C.
involvesWorkers
Indicates that an event, process, or situation includes workers as active participants or affected parties.
-
D.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
E.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
- 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_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. |
Created at: Feb. 28, 2026, 1:08 p.m.