Triple
T21936803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Timmons |
E541708
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Amanda Timmons
Amanda Timmons is best known as the wife of 98 Degrees singer Jeff Timmons.
|
E1552820
|
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: Amanda Timmons | Statement: [Jeff Timmons, spouse, Amanda Timmons]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amanda Timmons Context triple: [Jeff Timmons, spouse, Amanda Timmons]
-
A.
Amanda Rollins
Amanda Rollins is a fictional NYPD detective on Law & Order: Special Victims Unit who works closely with Olivia Benson on sex-crimes investigations.
-
B.
Amanda Clayton
Amanda Clayton is an American actress best known for her role in the crime drama television series "City on a Hill."
-
C.
Amanda Thompson
Amanda Thompson is a prominent member of the Thompson family, known for her public profile and contributions that have brought recognition to the family name.
-
D.
Amanda Brown
Amanda Brown is an Australian musician best known as the multi-instrumentalist and violinist for the indie rock band The Go-Betweens.
-
E.
Amanda Brown
Amanda Brown is an American author best known for writing the novel that inspired the hit film "Legally Blonde."
- 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: Amanda Timmons Triple: [Jeff Timmons, spouse, Amanda Timmons]
Generated description
Amanda Timmons is best known as the wife of 98 Degrees singer Jeff Timmons.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Amanda Timmons Target entity description: Amanda Timmons is best known as the wife of 98 Degrees singer Jeff Timmons.
-
A.
Amanda Rollins
Amanda Rollins is a fictional NYPD detective on Law & Order: Special Victims Unit who works closely with Olivia Benson on sex-crimes investigations.
-
B.
Amanda Clayton
Amanda Clayton is an American actress best known for her role in the crime drama television series "City on a Hill."
-
C.
Amanda Thompson
Amanda Thompson is a prominent member of the Thompson family, known for her public profile and contributions that have brought recognition to the family name.
-
D.
Amanda Brown
Amanda Brown is an American author best known for writing the novel that inspired the hit film "Legally Blonde."
-
E.
Amanda Brown
Amanda Brown is an Australian musician best known as the multi-instrumentalist and violinist for the indie rock band The Go-Betweens.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1241c909c81908644eb73baa9def1 |
completed | April 28, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b97fc2600819085486a9d540c9df3 |
completed | May 18, 2026, 10:51 p.m. |
| NEDg | Description generation | batch_6a0b9884cb548190958d16f42be4bea8 |
completed | May 18, 2026, 10:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b98e7887881909ec9cc4a2a2167c5 |
completed | May 18, 2026, 10:55 p.m. |
Created at: April 16, 2026, 7:54 p.m.