Triple
T8779556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bones McKinney |
E208689
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | McKinney |
E415444
|
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: McKinney | Statement: [Bones McKinney, familyName, McKinney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McKinney Context triple: [Bones McKinney, familyName, McKinney]
-
A.
McKinney
chosen
McKinney is a surname of Scottish and Irish origin borne by various notable individuals, including American politician and activist Cynthia McKinney.
-
B.
McKinney, Texas
McKinney, Texas is a rapidly growing suburban city in North Texas known for its historic downtown and high quality of life within the greater Dallas–Fort Worth area.
-
C.
Forney
Forney is a surname of German origin borne by various notable individuals, including engineers, politicians, and artists.
-
D.
Wimberley
Wimberley is a small, scenic town in central Texas known for its picturesque Hill Country landscapes, swimming holes, and artsy, tourist-friendly downtown.
-
E.
Frisco
Frisco is the popular nickname for the historic St. Louis–San Francisco Railway, a major American railroad that operated across the Midwest and South.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f548aa48190b2e73f292758e361 |
completed | March 31, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf51df4a608190883a093dbd169976 |
completed | April 3, 2026, 5:36 a.m. |
Created at: March 30, 2026, 6:42 p.m.