Triple
T20754324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexican Texas |
E510806
|
entity |
| Predicate | notableEmpresario |
P141366
|
FINISHED |
| Object | Green DeWitt |
—
|
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: Green DeWitt | Statement: [Mexican Texas, notableEmpresario, Green DeWitt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Green DeWitt Context triple: [Mexican Texas, notableEmpresario, Green DeWitt]
-
A.
Green DeWitt
chosen
Green DeWitt was an early 19th-century empresario who founded one of the major Anglo-American colonies in Mexican Texas, helping pave the way for increased U.S. settlement in the region.
-
B.
Calvin DeWitt
Calvin DeWitt is a notable individual distinguished enough to be recognized as a prominent bearer of the De Witt surname.
-
C.
Nelson DeWitt
Nelson DeWitt is an American documentary filmmaker and writer known for exploring themes of identity, family history, and personal discovery.
-
D.
John Livengood
John Livengood is the person after whom the place or entity named "Livengood" is derived, likely recognized as an early settler or notable figure associated with that name.
-
E.
Joseph McCasland
Joseph McCasland is a film editor known for his work on the comedy movie "Drunk Parents."
- 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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c22e0d288190ba924423af59d70d |
completed | April 21, 2026, 12:17 a.m. |
Created at: April 16, 2026, 12:34 p.m.