Triple
T12561144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Hamlin |
E295346
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Nicollette Sheridan |
E676862
|
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: Nicollette Sheridan | Statement: [Harry Hamlin, spouse, Nicollette Sheridan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicollette Sheridan Context triple: [Harry Hamlin, spouse, Nicollette Sheridan]
-
A.
Nicollette Sheridan
chosen
Nicollette Sheridan is a British-American actress best known for her roles on the television series "Knots Landing" and "Desperate Housewives."
-
B.
Gates McFadden
Gates McFadden is an American actress and choreographer best known for playing Dr. Beverly Crusher in the Star Trek franchise.
-
C.
Angela Richards
Angela Richards is known as one of the children of Rolling Stones guitarist Keith Richards.
-
D.
Elizabeth McGovern
Elizabeth McGovern is an American actress and musician best known for her roles in films like "Ragtime" and the television series "Downton Abbey."
-
E.
Dana Delany
Dana Delany is an American actress best known for her acclaimed work in television dramas such as "China Beach," for which she earned multiple Primetime Emmy Awards.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954933e7c819083471c627ce55ff1 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6718ef43481909023a82425283f5b |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 8, 2026, 11:48 p.m.