Triple
T9154504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Good Wife |
E219674
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object |
Michelle King
Michelle King is an American television writer and producer best known for co-creating the acclaimed legal and political drama series "The Good Wife."
|
E781255
|
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 King | Statement: [The Good Wife, creator, Michelle King]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michelle King Context triple: [The Good Wife, creator, Michelle King]
-
A.
Gail C. Murphy
Gail C. Murphy is a prominent Canadian computer scientist known for her influential research in software engineering, particularly in improving developer productivity and software evolution.
-
B.
Tina Kotek
Tina Kotek is an American politician and former state legislative leader who became the first openly lesbian governor in the United States.
-
C.
Janet Leahy
Janet Leahy is an American television writer and producer known for her work on acclaimed series such as Mad Men.
-
D.
Erinn Bartlett
Erinn Bartlett is an American actress and former beauty pageant titleholder known for supporting roles in film and television.
-
E.
Rachel Kelley
Rachel Kelley was the mother of Jesse Root Grant and the paternal grandmother of U.S. President Ulysses S. Grant.
- 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 King Triple: [The Good Wife, creator, Michelle King]
Generated description
Michelle King is an American television writer and producer best known for co-creating the acclaimed legal and political drama series "The Good Wife."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michelle King Target entity description: Michelle King is an American television writer and producer best known for co-creating the acclaimed legal and political drama series "The Good Wife."
-
A.
Gail C. Murphy
Gail C. Murphy is a prominent Canadian computer scientist known for her influential research in software engineering, particularly in improving developer productivity and software evolution.
-
B.
Tina Kotek
Tina Kotek is an American politician and former state legislative leader who became the first openly lesbian governor in the United States.
-
C.
Janet Leahy
Janet Leahy is an American television writer and producer known for her work on acclaimed series such as Mad Men.
-
D.
Erinn Bartlett
Erinn Bartlett is an American actress and former beauty pageant titleholder known for supporting roles in film and television.
-
E.
Rachel Kelley
Rachel Kelley was the mother of Jesse Root Grant and the paternal grandmother of U.S. President Ulysses S. Grant.
- 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_69ca83e25418819093c6503deeaf30de |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca96f87ac8190b2fc6d2b2834c1b6 |
completed | April 1, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0484e580c8190944ad76f6ef0be9d |
completed | April 3, 2026, 11:07 p.m. |
| NEDg | Description generation | batch_69d0496672a881909c1ac91a7ec1a2a1 |
completed | April 3, 2026, 11:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d04a35451881909dfe6795b743b026 |
completed | April 3, 2026, 11:16 p.m. |
Created at: March 30, 2026, 7:20 p.m.