Triple
T5166269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyle Talbot |
E116564
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Margaret Epple
Margaret Epple was the wife of American actor Lyle Talbot, known for their long marriage and family life together.
|
E552446
|
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: Margaret Epple | Statement: [Lyle Talbot, spouse, Margaret Epple]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margaret Epple Context triple: [Lyle Talbot, spouse, Margaret Epple]
-
A.
Margaret Rudkin
Margaret Rudkin was an American businesswoman and food industry pioneer best known for building Pepperidge Farm from a home baking venture into a major commercial bakery brand.
-
B.
Marjorie Hearn
Marjorie Hearn was the longtime wife and partner of legendary Los Angeles Lakers broadcaster Chick Hearn.
-
C.
Mary Morris
Mary "May" Morris was a British artisan, designer, and influential figure in the Arts and Crafts movement, known especially for her innovative embroidery and textile work.
-
D.
Margaret Cox
Margaret Cox is known as the daughter of British physicist and science communicator Brian Cox.
-
E.
Mary Margaret Farabee
Mary Margaret Farabee was a Texas cultural leader and philanthropist best known for co-founding the Texas Book Festival to promote literature and support libraries.
- 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: Margaret Epple Triple: [Lyle Talbot, spouse, Margaret Epple]
Generated description
Margaret Epple was the wife of American actor Lyle Talbot, known for their long marriage and family life together.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Margaret Epple Target entity description: Margaret Epple was the wife of American actor Lyle Talbot, known for their long marriage and family life together.
-
A.
Margaret Rudkin
Margaret Rudkin was an American businesswoman and food industry pioneer best known for building Pepperidge Farm from a home baking venture into a major commercial bakery brand.
-
B.
Marjorie Hearn
Marjorie Hearn was the longtime wife and partner of legendary Los Angeles Lakers broadcaster Chick Hearn.
-
C.
Mary Morris
Mary "May" Morris was a British artisan, designer, and influential figure in the Arts and Crafts movement, known especially for her innovative embroidery and textile work.
-
D.
Margaret Cox
Margaret Cox is known as the daughter of British physicist and science communicator Brian Cox.
-
E.
Mary Margaret Farabee
Mary Margaret Farabee was a Texas cultural leader and philanthropist best known for co-founding the Texas Book Festival to promote literature and support libraries.
- 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_69bd445edb3881909b93b34d260717fc |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd792c5ea88190b6aa0e519c744155 |
completed | March 20, 2026, 4:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b0779eec81909793446efb2ce749 |
completed | March 23, 2026, 3:16 a.m. |
| NEDg | Description generation | batch_69c0b1c9ebdc819089752d150b584a6f |
completed | March 23, 2026, 3:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0b27981848190a5b7c618044241b0 |
completed | March 23, 2026, 3:24 a.m. |
Created at: March 20, 2026, 1:44 p.m.