Triple
T8291565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Time for Love |
E193908
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Mary Field
Mary Field was an American character actress known for her numerous supporting roles in Hollywood films from the 1930s through the 1950s.
|
E723482
|
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: Mary Field | Statement: [No Time for Love, castMember, Mary Field]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Field Context triple: [No Time for Love, castMember, Mary Field]
-
A.
Virginia Fields
Virginia Fields is known as the wife of legendary American football coach and broadcaster John Madden.
-
B.
May Field
May Field is an equestrian sports venue that hosted the equestrian events of the 1936 Summer Olympics in Berlin.
-
C.
Jamie Fields
Jamie Fields is a central teenage character in the 2016 coming-of-age film "20th Century Women," navigating identity, relationships, and adulthood in late-1970s California.
-
D.
Mary Wheeler
Mary Wheeler is a sibling of the renowned American theoretical physicist John Archibald Wheeler.
-
E.
Mary Lynn
Mary Lynn is an American actress and comedian best known for her role as computer analyst Chloe O'Brian on the television series "24."
- 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: Mary Field Triple: [No Time for Love, castMember, Mary Field]
Generated description
Mary Field was an American character actress known for her numerous supporting roles in Hollywood films from the 1930s through the 1950s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Field Target entity description: Mary Field was an American character actress known for her numerous supporting roles in Hollywood films from the 1930s through the 1950s.
-
A.
Virginia Fields
Virginia Fields is known as the wife of legendary American football coach and broadcaster John Madden.
-
B.
May Field
May Field is an equestrian sports venue that hosted the equestrian events of the 1936 Summer Olympics in Berlin.
-
C.
Jamie Fields
Jamie Fields is a central teenage character in the 2016 coming-of-age film "20th Century Women," navigating identity, relationships, and adulthood in late-1970s California.
-
D.
Mary Wheeler
Mary Wheeler is a sibling of the renowned American theoretical physicist John Archibald Wheeler.
-
E.
Mary Lynn
Mary Lynn is an American actress and comedian best known for her role as computer analyst Chloe O'Brian on the television series "24."
- 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_69ca82e32db481908b72f3804fa71152 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7c9b65e0819083ddc82fb7c4a5f3 |
completed | March 31, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd68916c5481908c42f259298b0670 |
completed | April 1, 2026, 6:48 p.m. |
| NEDg | Description generation | batch_69cd6d567c3c81908a7ec5bc13be529d |
completed | April 1, 2026, 7:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd7e3e2f848190a22ad8739bb8e298 |
completed | April 1, 2026, 8:21 p.m. |
Created at: March 30, 2026, 5:52 p.m.