Triple
T5213416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arts, Beats & Eats festival |
E117687
|
entity |
| Predicate | foodVendors |
P50801
|
FINISHED |
| Object | local restaurants |
—
|
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: local restaurants | Statement: [Arts, Beats & Eats festival, foodVendors, local restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foodVendors Context triple: [Arts, Beats & Eats festival, foodVendors, local restaurants]
-
A.
hasFoodVendors
chosen
Indicates that one entity provides or hosts food vendors that operate at or within another entity.
-
B.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
-
C.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
D.
foodSources
Indicates a relationship where one entity serves as a source of food or nourishment for another entity.
-
E.
hasStreetFood
Indicates that one entity offers, features, or is associated with street food in relation to another 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_69bd4464ba3c8190bc16b2ebbe42ddb0 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a911d40819086621537274dc0f0 |
completed | March 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:47 p.m.