Triple
T17223121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sela Ward |
E418038
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Howard Sherman |
—
|
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: Howard Sherman | Statement: [Sela Ward, spouse, Howard Sherman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard Sherman Context triple: [Sela Ward, spouse, Howard Sherman]
-
A.
Howard Sherman
chosen
Howard Sherman is an American businessman and film producer best known as the husband of actress Sela Ward.
-
B.
Howard Sherman
Howard Sherman is a relatively obscure individual primarily known in available records through his familial connection to Anabella Sherman.
-
C.
Bruce Sherman
Bruce Sherman is an American businessman and investor best known as the principal owner and chairman of Major League Baseball’s Miami Marlins.
-
D.
Fred Schuler
Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
-
E.
Howard Marner
Howard Marner is a character in the science-fiction comedy film "Short Circuit," serving as one of the key figures involved with the experimental military robots central to the story.
- 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_69d886d779488190b131369541c04e7d |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42ddf2c3c8190b6adceaaefd4ccbf |
completed | April 19, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:38 a.m.