Triple
T18691439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walt Weiss |
E457010
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Walt Weiss |
—
|
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: Walt Weiss | Statement: [Walt Weiss, name, Walt Weiss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walt Weiss Context triple: [Walt Weiss, name, Walt Weiss]
-
A.
Walt Weiss
chosen
Walt Weiss is a former Major League Baseball shortstop and later manager, best known for his early success with the Oakland Athletics and his long career in professional baseball.
-
B.
Brandon Merrill
Brandon Merrill is an American model and actress best known for her role as the Native American woman Falling Leaves in the Jackie Chan–Owen Wilson Western comedy film "Shanghai Noon."
-
C.
Albert Pinson
Albert Pinson was a 19th-century English officer best known for his passionate and scandalous love affair with Adèle Hugo, the daughter of French writer Victor Hugo.
-
D.
Elmer Flick
Elmer Flick was an American Major League Baseball outfielder and Hall of Famer known for his exceptional hitting and base-stealing in the early 20th century.
-
E.
Brett Keller
Brett Keller is the chief executive officer of Priceline, a major online travel booking company.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e3a6d08190b2409bcbf0c42444 |
completed | April 19, 2026, 11:18 p.m. |
Created at: April 10, 2026, 11:49 a.m.