Triple
T10522238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulsa metropolitan area |
E248202
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object | Jenks |
E739316
|
NE 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: Jenks | Statement: [Tulsa metropolitan area, includesCity, Jenks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jenks Context triple: [Tulsa metropolitan area, includesCity, Jenks]
-
A.
Jenks
chosen
Jenks is a small city in northeastern Oklahoma, known as a suburb of Tulsa and part of the region often called Green Country.
-
B.
Kanesville
Kanesville was the mid-19th-century Mormon settlement that later became the city of Council Bluffs, Iowa.
-
C.
Midland City
Midland City is a fictional Midwestern American town created by Kurt Vonnegut that serves as the primary setting for several of his novels.
-
D.
Tecumseh, Kansas
Tecumseh, Kansas is a small unincorporated community in northeastern Kansas, located just east of Topeka along the Kansas River.
-
E.
Hutchinson
Hutchinson is a common English surname borne by numerous notable individuals across fields such as science, politics, and the arts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509e0907481908807dd99980cba1f |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90e119fe4819085e5c1c6e71e6260 |
completed | April 10, 2026, 2:49 p.m. |
Created at: April 6, 2026, 12:29 p.m.