Triple
T23030826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cumberland, Oklahoma |
E573449
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Oklahoma |
—
|
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: Oklahoma | Statement: [Cumberland, Oklahoma, partOf, Oklahoma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oklahoma Context triple: [Cumberland, Oklahoma, partOf, Oklahoma]
-
A.
Oklahoma
chosen
Oklahoma is a landlocked state in the south-central United States known for its Native American heritage, energy industry, and mix of Great Plains and forested landscapes.
-
B.
Kansas, Alabama
Kansas, Alabama is a small unincorporated rural community located in Walker County in the U.S. state of Alabama.
-
C.
Teksas
Teksas is the famously passionate and vocal supporter group of the Turkish football club Bursaspor, known for its intense atmosphere and choreographies at matches.
-
D.
Texas
Texas is a Scottish pop rock band known for their melodic, radio-friendly hits and enduring success since the late 1980s.
-
E.
Texas
Texas is the second-largest U.S. state by both area and population, known for its diverse landscapes, major cities like Houston and Dallas, and significant cultural and economic influence.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b911188190bc3d96326c847969 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18481072c81909ab2a2c87e034433 |
completed | April 29, 2026, 4:09 a.m. |
Created at: April 17, 2026, 3:53 p.m.