Triple
T18387871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tarte flambée |
E446638
|
entity |
| Predicate | traditionalConsumptionContext |
P97073
|
FINISHED |
| Object | shared among several people |
—
|
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: shared among several people | Statement: [tarte flambée, traditionalConsumptionContext, shared among several people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalConsumptionContext Context triple: [tarte flambée, traditionalConsumptionContext, shared among several people]
-
A.
primaryConsumptionContext
Indicates the main situation, setting, or context in which something is typically used, consumed, or experienced.
-
B.
consumptionMethod
Indicates the manner or process by which something is consumed, used up, or ingested.
-
C.
typicalSettingConsumed
chosen
Indicates the usual context or environment in which something is normally consumed.
-
D.
commonlyConsumedAt
Indicates that one entity is typically eaten or drunk during, or in association with, a particular time, event, or context.
-
E.
isTypicallyConsumedFrom
Indicates that one entity is most commonly eaten or drunk using, contained in, or taken from the other entity.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e517a114c08190af1be1ae52c83b63 |
completed | April 19, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69e44ff1f92c8190afbb8e85d12bf2a9 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:46 a.m.