Triple
T8147258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klyde Warren |
E190244
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Klyde Warren |
E190244
|
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: Klyde Warren | Statement: [Klyde Warren, name, Klyde Warren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klyde Warren Context triple: [Klyde Warren, name, Klyde Warren]
-
A.
Klyde Warren
chosen
Klyde Warren is the namesake of Dallas’s Klyde Warren Park, a prominent urban green space built over a freeway in the city’s downtown area.
-
B.
Larry Kennar
Larry Kennar is a television producer best known for his executive production work on the groundbreaking LGBTQ+ drama series "The L Word."
-
C.
John Culberson
John Culberson is an American Republican politician and attorney who represented Texas in the U.S. House of Representatives from 2001 to 2019.
-
D.
John Gamble Kirkwood
John Gamble Kirkwood was an influential American theoretical chemist and physicist known for his foundational contributions to statistical mechanics and the theory of liquids.
-
E.
John Canada Terrell
John Canada Terrell is an American actor best known for his starring role in Spike Lee’s breakthrough 1986 film "She’s Gotta Have It."
- 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_69ca82be7ba8819087de0147e9292c83 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb447d6b1881908ff3fa25af6b4e80 |
completed | March 31, 2026, 3:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc94b667d88190a0b47c7e0e07f338 |
completed | April 1, 2026, 3:44 a.m. |
Created at: March 30, 2026, 5:36 p.m.