Triple
T665769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pkhali |
E12856
|
entity |
| Predicate | consumptionOccasion |
P14787
|
FINISHED |
| Object | festive meals |
—
|
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: festive meals | Statement: [Pkhali, consumptionOccasion, festive meals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consumptionOccasion Context triple: [Pkhali, consumptionOccasion, festive meals]
-
A.
servingOccasion
chosen
Indicates the occasion, event, or context during which something (typically food or drink) is served.
-
B.
primaryOccasion
Indicates that one occasion is the main or most significant event associated with a given context, entity, or activity.
-
C.
displayOccasion
Indicates the event, context, or situation during which something is presented, shown, or made visible.
-
D.
eatenOnOccasion
Indicates that one entity is consumed or eaten by another only at certain times or under specific circumstances, rather than regularly or habitually.
-
E.
consumptionMethod
Indicates the manner or process by which something is consumed, used up, or ingested.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fd4f4988190a0973ceb7329b4c9 |
completed | March 1, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69a49d16cff881908c8d2c3fe4d1d6fb |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.