Triple
T3761917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albuquerque International Balloon Fiesta |
E82180
|
entity |
| Predicate | hasFoodVendors |
P50801
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Albuquerque International Balloon Fiesta, hasFoodVendors, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFoodVendors Context triple: [Albuquerque International Balloon Fiesta, hasFoodVendors, yes]
-
A.
hasStreetFood
Indicates that one entity offers, features, or is associated with street food in relation to another entity.
-
B.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
-
C.
hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
-
D.
hasSpecialtyFood
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
-
E.
eatingPermitted
Indicates that an entity is allowed or authorized to eat in a given context or situation.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbfa44ac819082f2c895d96c9170 |
completed | March 8, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69adc04c851c8190ae5eaebf36df539b |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc0fe3e3c8190bd886c7745c172a0 |
completed | March 8, 2026, 6:33 p.m. |
Created at: March 8, 2026, 3:35 p.m.