Triple
T13542380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Greenwood |
E323418
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Kimberly Payne
Kimberly Payne is best known as the wife of American country music singer Lee Greenwood.
|
E1166174
|
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: Kimberly Payne | Statement: [Lee Greenwood, spouse, Kimberly Payne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kimberly Payne Context triple: [Lee Greenwood, spouse, Kimberly Payne]
-
A.
Kimberly Reese
Kimberly Reese is a diligent, ambitious college student and close friend of Whitley Gilbert on the sitcom "A Different World," known for her academic drive and grounded personality.
-
B.
Kimberly Parker
Kimberly Parker is a film producer known for her work on the 2013 drama "A Teacher."
-
C.
Kimberly Drummond
Kimberly Drummond is a central character on the American sitcom "Diff'rent Strokes," known as the teenage daughter in the wealthy Drummond family who helps bridge the cultural gap with her adopted brothers.
-
D.
Nessa Jenkins
Nessa Jenkins is a deadpan, no-nonsense Welsh character from the British sitcom "Gavin & Stacey," known for her eccentric stories and iconic catchphrases.
-
E.
Nicole Parker
Nicole Parker is an American actress and comedian best known for her sketch work on MADtv and roles in parody films.
- 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: Kimberly Payne Triple: [Lee Greenwood, spouse, Kimberly Payne]
Generated description
Kimberly Payne is best known as the wife of American country music singer Lee Greenwood.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kimberly Payne Target entity description: Kimberly Payne is best known as the wife of American country music singer Lee Greenwood.
-
A.
Kimberly Reese
Kimberly Reese is a diligent, ambitious college student and close friend of Whitley Gilbert on the sitcom "A Different World," known for her academic drive and grounded personality.
-
B.
Kimberly Parker
Kimberly Parker is a film producer known for her work on the 2013 drama "A Teacher."
-
C.
Kimberly Drummond
Kimberly Drummond is a central character on the American sitcom "Diff'rent Strokes," known as the teenage daughter in the wealthy Drummond family who helps bridge the cultural gap with her adopted brothers.
-
D.
Nessa Jenkins
Nessa Jenkins is a deadpan, no-nonsense Welsh character from the British sitcom "Gavin & Stacey," known for her eccentric stories and iconic catchphrases.
-
E.
Nicole Parker
Nicole Parker is an American actress and comedian best known for her sketch work on MADtv and roles in parody films.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafd8ba10819098faadcc6adf251e |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56ade75c8190b556c3b0ba692a96 |
completed | May 9, 2026, 3:45 p.m. |
| NEDg | Description generation | batch_69ff5858f6f88190a94a871c831e4f78 |
completed | May 9, 2026, 3:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff589de85c8190abc9c888ac90cf52 |
completed | May 9, 2026, 3:54 p.m. |
Created at: April 9, 2026, 9:45 p.m.