Triple
T25223382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BET Award for Best Movie |
E632021
|
entity |
| Predicate | typicalEligibilityRegion |
P24526
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [BET Award for Best Movie, typicalEligibilityRegion, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEligibilityRegion Context triple: [BET Award for Best Movie, typicalEligibilityRegion, United States]
-
A.
eligibleRegion
chosen
Indicates the geographic area within which something (such as an offer, service, or rule) is valid, applicable, or permitted.
-
B.
includesUSRegions
Indicates that something contains or covers one or more specified regions within the United States.
-
C.
issuerRegionServed
Indicates the geographic region or area that the issuer provides services to or operates within.
-
D.
ISORegion
Indicates a standardized geographic or administrative region as defined by an ISO (International Organization for Standardization) code.
-
E.
includedRegions
Indicates that certain regions are contained within, or form part of, a larger specified region or set of regions.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: April 21, 2026, 1:03 p.m.