Triple
T2522959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rivers |
E55565
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Melissa Rivers
Melissa Rivers is an American television host, producer, and actress best known for her red carpet coverage and for continuing the comedic legacy of her mother, Joan Rivers.
|
E398546
|
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: Melissa Rivers | Statement: [Rivers, hasNotableBearer, Melissa Rivers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melissa Rivers Context triple: [Rivers, hasNotableBearer, Melissa Rivers]
-
A.
Melissa Kent
Melissa Kent is a film editor known for her work on feature films such as the romantic comedy "Just Wright."
-
B.
Melissa Mathison
Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
-
C.
Melinda Rogers
Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
-
D.
Lindy Robbins
Lindy Robbins is an American songwriter known for crafting hit pop songs for major artists across the contemporary music industry.
-
E.
Rebecca Calhoun
Rebecca Calhoun was the wife of American Revolutionary War general and South Carolina politician Andrew Pickens.
- 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: Melissa Rivers Triple: [Rivers, hasNotableBearer, Melissa Rivers]
Generated description
Melissa Rivers is an American television host, producer, and actress best known for her red carpet coverage and for continuing the comedic legacy of her mother, Joan Rivers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Melissa Rivers Target entity description: Melissa Rivers is an American television host, producer, and actress best known for her red carpet coverage and for continuing the comedic legacy of her mother, Joan Rivers.
-
A.
Melissa Kent
Melissa Kent is a film editor known for her work on feature films such as the romantic comedy "Just Wright."
-
B.
Melissa Mathison
Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
-
C.
Melinda Rogers
Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
-
D.
Lindy Robbins
Lindy Robbins is an American songwriter known for crafting hit pop songs for major artists across the contemporary music industry.
-
E.
Rebecca Calhoun
Rebecca Calhoun was the wife of American Revolutionary War general and South Carolina politician Andrew Pickens.
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd23a0a548190b44393e0f823f7a9 |
completed | March 7, 2026, 7:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b528071e488190ac531404dac9587c |
completed | March 14, 2026, 9:19 a.m. |
| NEDg | Description generation | batch_69b528d33c2081908e5f74005679dfbe |
completed | March 14, 2026, 9:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5294c66588190ad7cc8e87b58ff52 |
completed | March 14, 2026, 9:24 a.m. |
Created at: March 6, 2026, 9:46 p.m.