Triple
T16415430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Thompson Walters |
E398671
|
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: [William Thompson Walters, familyName, Walters]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walters Context triple: [William Thompson 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 masculine given name of Germanic origin that has been widely used in English-speaking countries.
-
C.
Walter
Walter is the central figure known as "The Woodsman," a character defined by his rugged life in the forest and the moral or psychological struggles that accompany his isolation.
-
D.
Walter
Walter is a grumpy, sharp-tongued old-man puppet character featured in Jeff Dunham’s stand-up comedy acts.
-
E.
Waller
Waller is a surname most notably associated with American author Robert James Waller, known for writing "The Bridges of Madison County."
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e3287741008190856882b7f34024fc |
completed | April 18, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c6a89988190a44515f1ca08099f |
completed | May 10, 2026, 8:06 a.m. |
Created at: April 10, 2026, 5:09 a.m.