Triple
T8388140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Whitmore |
E197871
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Noreen Nash
Noreen Nash was an American film actress who appeared in numerous Hollywood productions during the 1940s and 1950s.
|
E865982
|
NE FINISHED |
How this triple was built (4 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: Noreen Nash | Statement: [James Whitmore, spouse, Noreen Nash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noreen Nash Context triple: [James Whitmore, spouse, Noreen Nash]
-
A.
Nora Mellon
Nora Mellon was a member of the prominent Mellon family after whom the industrial town of Donora, Pennsylvania, was named.
-
B.
Nancy Morgan
Nancy Morgan is an American actress known for her film and television work and for her former marriage to actor John Ritter.
-
C.
Rose Nylund
Rose Nylund is a sweet, naive, and hilariously literal-minded Midwestern woman portrayed by Betty White on the classic sitcom "The Golden Girls."
-
D.
Nancy Wyman
Nancy Wyman is an American Democratic politician who served as the 108th lieutenant governor of Connecticut and previously chaired the state’s Democratic Party.
-
E.
Jane Cashion
Jane Cashion is known as the wife of longtime NFL referee Red Cashion.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Noreen Nash Triple: [James Whitmore, spouse, Noreen Nash]
Generated description
Noreen Nash was an American film actress who appeared in numerous Hollywood productions during the 1940s and 1950s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Noreen Nash Target entity description: Noreen Nash was an American film actress who appeared in numerous Hollywood productions during the 1940s and 1950s.
-
A.
Nora Mellon
Nora Mellon was a member of the prominent Mellon family after whom the industrial town of Donora, Pennsylvania, was named.
-
B.
Nancy Morgan
Nancy Morgan is an American actress known for her film and television work and for her former marriage to actor John Ritter.
-
C.
Rose Nylund
Rose Nylund is a sweet, naive, and hilariously literal-minded Midwestern woman portrayed by Betty White on the classic sitcom "The Golden Girls."
-
D.
Nancy Wyman
Nancy Wyman is an American Democratic politician who served as the 108th lieutenant governor of Connecticut and previously chaired the state’s Democratic Party.
-
E.
Jane Cashion
Jane Cashion is known as the wife of longtime NFL referee Red Cashion.
- F. None of above. chosen
Provenance (5 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_69ca82f749388190bffbea6dfb509016 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb81090f688190a3a8d1680383c361 |
completed | March 31, 2026, 8:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89eedc66c81909076cc7ba35f9da5 |
completed | April 10, 2026, 6:55 a.m. |
| NEDg | Description generation | batch_69d8a2f4bbec8190a5c508c6431d71b2 |
completed | April 10, 2026, 7:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d8aff34c7081909c3504e00f56d9ec |
completed | April 10, 2026, 8:08 a.m. |
Created at: March 30, 2026, 6:03 p.m.