Triple
T11116799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vernon A. Walters |
E262906
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Walters |
E531865
|
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: Walters | Statement: [Vernon A. Walters, familyName, Walters]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walters Context triple: [Vernon A. Walters, familyName, Walters]
-
A.
Walters
chosen
Walters is a common English surname borne by numerous notable individuals across fields such as acting, politics, and sports.
-
B.
Walter
Walter is a grumpy, sharp-tongued old-man puppet character featured in Jeff Dunham’s stand-up comedy acts.
-
C.
Walter
Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
-
D.
Waller
Waller is a surname most notably associated with American author Robert James Waller, known for writing "The Bridges of Madison County."
-
E.
Wilkerson
Wilkerson is the surname of Muhammad Wilkerson, an American former NFL defensive end best known for his Pro Bowl tenure with the New York Jets.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79aa81d8c81908a387b56cbcc9128 |
completed | April 9, 2026, 12:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d8084a88190918f1f94ca0119ed |
completed | April 19, 2026, 1:18 a.m. |
Created at: April 8, 2026, 9:27 p.m.