Triple
T3143002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cirón |
E65695
|
entity |
| Predicate | helpsProduce |
P45631
|
FINISHED |
| Object | sweet white wines of Sauternes |
—
|
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: sweet white wines of Sauternes | Statement: [Cirón, helpsProduce, sweet white wines of Sauternes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsProduce Context triple: [Cirón, helpsProduce, sweet white wines of Sauternes]
-
A.
produces
Indicates that one entity creates, generates, or yields another entity as a result or output.
-
B.
increasesProductionOf
Indicates that one entity causes a rise or enhancement in the amount or rate at which another entity is produced.
-
C.
producesFor
Indicates that one entity creates, manufactures, or generates something specifically intended for another entity’s use, benefit, or distribution.
-
D.
includesProduce
Indicates that one entity contains or offers certain produce items as part of its contents, inventory, or offerings.
-
E.
hasProduction
Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
- 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada59489a88190b0962cef091f4ddb |
completed | March 8, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69ad9df840088190a26a1516f4c1f056 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f7c21c819087e9992f5fe30a37 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:05 p.m.