Triple
T8689065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayonne ham |
E206237
|
entity |
| Predicate | traditionality |
P64101
|
FINISHED |
| Object | centuries-old production tradition |
—
|
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: centuries-old production tradition | Statement: [Bayonne ham, traditionality, centuries-old production tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionality Context triple: [Bayonne ham, traditionality, centuries-old production tradition]
-
A.
establishedTradition
chosen
Indicates that something has become a customary, long-standing practice or convention that is regularly followed within a group, culture, or context.
-
B.
mainTradition
Indicates that one entity represents the primary or dominant tradition associated with another entity.
-
C.
uniformTradition
Indicates that multiple entities follow the same established customs, practices, or conventions in a consistent manner.
-
D.
traditionAscribes
Indicates that a tradition attributes or assigns a particular quality, role, origin, or action to an entity.
-
E.
traditionSince
Indicates that a tradition has been continuously practiced or recognized starting from a specified point in time.
- 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc57334b0c8190903a5a1784e74791 |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc4569f9048190b9c86b4c81103d35 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:33 p.m.