Triple
T15492163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walt Whitman (actor) |
E378713
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Walt |
E32053
|
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: Walt | Statement: [Walt Whitman (actor), hasGivenName, Walt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walt Context triple: [Walt Whitman (actor), hasGivenName, Walt]
-
A.
Walter
Walter is a grumpy, sharp-tongued old-man puppet character featured in Jeff Dunham’s stand-up comedy acts.
-
B.
Walter
chosen
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.
Walt Lloyd
Walt Lloyd is an American cinematographer known for his work on independent and studio films, including the cult classic "Pump Up the Volume."
-
E.
Wally
Wally is a character from the comedy film "The Great Outdoors," known for his role in the movie’s humorous family vacation mishaps.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fac2af88190ac1d119e6b21dbe0 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3660fc6c81908caf1729260a8338 |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:49 a.m.