Triple
T6205825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lancaster, Texas |
E138742
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | A. Bledsoe |
E134500
|
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: A. Bledsoe | Statement: [Lancaster, Texas, foundedBy, A. Bledsoe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A. Bledsoe Context triple: [Lancaster, Texas, foundedBy, A. Bledsoe]
-
A.
A. Bledsoe
chosen
A. Bledsoe was an early settler and community leader credited with establishing the town of Lancaster in Texas.
-
B.
Bledsoe
Bledsoe is a surname most notably associated with American professional basketball player Eric Bledsoe.
-
C.
Frank Bledsoe
Frank Bledsoe is the closeted gay literature professor at the center of the film "Uncle Frank," whose road trip with his niece forces him to confront his past and his Southern family's prejudices.
-
D.
Cecil Gaines
Cecil Gaines is the fictionalized African-American White House butler whose life story, spanning decades of service to multiple U.S. presidents, is portrayed in the film "The Butler."
-
E.
Mr. Porter
Mr. Porter is an American hip-hop producer and rapper best known as a longtime member of D12 and frequent collaborator of Eminem.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626f85748190a94448117a85fd78 |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f47b04c81909bfe20305911f5f2 |
completed | March 23, 2026, 4:50 p.m. |
Created at: March 22, 2026, 4:20 p.m.