Triple
T3614866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allstate Sugar Bowl |
E76574
|
entity |
| Predicate | economicImpactOnCity |
P40344
|
FINISHED |
| Object | major tourism event for New Orleans |
—
|
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: major tourism event for New Orleans | Statement: [Allstate Sugar Bowl, economicImpactOnCity, major tourism event for New Orleans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicImpactOnCity Context triple: [Allstate Sugar Bowl, economicImpactOnCity, major tourism event for New Orleans]
-
A.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
-
B.
localEconomyImpact
chosen
Indicates the effect that an action, event, or entity has on the economic conditions, activities, or performance of a specific local area or community.
-
C.
affectedCity
Indicates that a particular city is impacted or influenced by a specified event, action, or condition.
-
D.
economicDamage
Indicates that one entity causes or experiences financial loss, harm, or negative economic impact as a result of another entity or event.
-
E.
covid19Impact
Indicates the effect, consequences, or influence that COVID-19 has on a given entity, condition, or situation.
- 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_69ad85da0ba481908b3b48c69efe2b98 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc279f6948190b9655a4cf3e77d89 |
completed | March 8, 2026, 6:39 p.m. |
| PD | Predicate disambiguation | batch_69adb83f1e4c8190ab501c1c05b14c08 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:23 p.m.