Triple
T8881376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Glor |
E211417
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Nicole Glor
Nicole Glor is a fitness instructor, author, and media personality known for her workout programs and marriage to journalist Jeff Glor.
|
E807106
|
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: Nicole Glor | Statement: [Jeff Glor, spouse, Nicole Glor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicole Glor Context triple: [Jeff Glor, spouse, Nicole Glor]
-
A.
Nicole Lyn
Nicole Lyn is a Canadian actress best known for her work in television series such as "Student Bodies" and various film and voice roles.
-
B.
Nicole D'Ovidio
Nicole D'Ovidio is a screenwriter best known for crafting the story for the 2013 thriller film "The Call."
-
C.
Nicole Durant
Nicole Durant is a supporting character in the 2006 comedy film "The Pink Panther," involved in the mystery surrounding the famous diamond theft.
-
D.
Nicole Fugere
Nicole Fugere is an American actress best known for playing Wednesday Addams in late-1990s Addams Family television projects.
-
E.
Aimee Garcia
Aimee Garcia is an American actress best known for her television roles on shows like "Dexter" and "Lucifer," as well as her work in film and voice acting.
- 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: Nicole Glor Triple: [Jeff Glor, spouse, Nicole Glor]
Generated description
Nicole Glor is a fitness instructor, author, and media personality known for her workout programs and marriage to journalist Jeff Glor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nicole Glor Target entity description: Nicole Glor is a fitness instructor, author, and media personality known for her workout programs and marriage to journalist Jeff Glor.
-
A.
Nicole Lyn
Nicole Lyn is a Canadian actress best known for her work in television series such as "Student Bodies" and various film and voice roles.
-
B.
Nicole D'Ovidio
Nicole D'Ovidio is a screenwriter best known for crafting the story for the 2013 thriller film "The Call."
-
C.
Nicole Durant
Nicole Durant is a supporting character in the 2006 comedy film "The Pink Panther," involved in the mystery surrounding the famous diamond theft.
-
D.
Nicole Fugere
Nicole Fugere is an American actress best known for playing Wednesday Addams in late-1990s Addams Family television projects.
-
E.
Aimee Garcia
Aimee Garcia is an American actress best known for her television roles on shows like "Dexter" and "Lucifer," as well as her work in film and voice acting.
- 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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6168e3d881908c58cf11cf5f9a0e |
completed | April 1, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d152541308819098cdca4f3ba9011d |
completed | April 4, 2026, 6:03 p.m. |
| NEDg | Description generation | batch_69d155488e948190889abf1c8d0c926d |
completed | April 4, 2026, 6:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d155a460e88190a9fd4ba2a59f80ca |
completed | April 4, 2026, 6:17 p.m. |
Created at: March 30, 2026, 6:53 p.m.