Triple
T15905192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary-Kate Olsen |
E385693
|
entity |
| Predicate | portrayed |
P1668
|
FINISHED |
| Object |
Michelle Tanner
Michelle Tanner is the youngest daughter in the Tanner family and a central, comedic character on the American sitcom "Full House."
|
E1183540
|
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: Michelle Tanner | Statement: [Mary-Kate Olsen, portrayed, Michelle Tanner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michelle Tanner Context triple: [Mary-Kate Olsen, portrayed, Michelle Tanner]
-
A.
Lisa Rogers
Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
-
B.
Tina Barrett
Tina Barrett is a British singer, songwriter, and dancer best known as a member of the pop group S Club 7.
-
C.
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.
-
D.
Melissa Fletcher
Melissa Fletcher is a Welsh former professional footballer known for playing as a forward for Reading FC Women and the Wales national team.
-
E.
Meredith Brown
Meredith Brown is a fictional character known as the sister of Velvet Brown in Enid Bagnold’s novel "National Velvet."
- 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: Michelle Tanner Triple: [Mary-Kate Olsen, portrayed, Michelle Tanner]
Generated description
Michelle Tanner is the youngest daughter in the Tanner family and a central, comedic character on the American sitcom "Full House."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michelle Tanner Target entity description: Michelle Tanner is the youngest daughter in the Tanner family and a central, comedic character on the American sitcom "Full House."
-
A.
Lisa Rogers
Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
-
B.
Tina Barrett
Tina Barrett is a British singer, songwriter, and dancer best known as a member of the pop group S Club 7.
-
C.
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.
-
D.
Melissa Fletcher
Melissa Fletcher is a Welsh former professional footballer known for playing as a forward for Reading FC Women and the Wales national team.
-
E.
Meredith Brown
Meredith Brown is a fictional character known as the sister of Velvet Brown in Enid Bagnold’s novel "National Velvet."
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1565956588190ba4726a2879b677d |
completed | April 16, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb0535a808190983b4ff028826cbf |
completed | May 9, 2026, 10:08 p.m. |
| NEDg | Description generation | batch_69ffb110a5b88190904f763057e8eb1e |
completed | May 9, 2026, 10:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb1a5e9b88190b790c81b9500c2ac |
completed | May 9, 2026, 10:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.