Triple
T3200540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Grill |
E67037
|
entity |
| Predicate | mealPeriod |
P46097
|
FINISHED |
| Object | dinner |
—
|
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: dinner | Statement: [California Grill, mealPeriod, dinner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mealPeriod Context triple: [California Grill, mealPeriod, dinner]
-
A.
workPeriod
Indicates the span of time during which an entity is engaged in a particular work or employment activity.
-
B.
workSettingPeriod
Indicates the time period during which a particular work setting or employment context is in effect.
-
C.
servedDuring
Indicates that one entity held a role, position, or performed a function within the time period defined by another entity.
-
D.
hasWorkPeriod
Indicates that an entity is associated with a specific span of time during which it performs or is engaged in some work or activity.
-
E.
regularTimeScore
Indicates the score or performance measure achieved during the standard or non-extended time period of an event or activity.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9aedef08190824bdf508f85f06f |
completed | March 8, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69ad9e05e4f48190adbe4366cdba2349 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f9259c8190afbc5ad0fa55436b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:07 p.m.