Triple
T7990784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melissa McBride |
E185999
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Melissa McBride |
E185999
|
NE FINISHED |
How this triple was built (2 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 McBride | Statement: [Melissa McBride, name, Melissa McBride]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melissa McBride Context triple: [Melissa McBride, name, Melissa McBride]
-
A.
Melissa McBride
chosen
Melissa McBride is an American actress best known for her acclaimed portrayal of Carol Peletier on the television series "The Walking Dead."
-
B.
Amy Acker
Amy Acker is an American actress best known for her roles in television series such as "Angel," "Person of Interest," and "Dollhouse."
-
C.
Allison Mack
Allison Mack is an American actress best known for her role as Chloe Sullivan on the television series "Smallville."
-
D.
Karen Rodriguez
Karen Rodriguez is an actress known for her role in the television series "Swarm."
-
E.
Melissa Cobb
Melissa Cobb is an American film producer best known for her work on major animated features, including the Kung Fu Panda franchise.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c6fc19c8190b98023e257c2f4f2 |
completed | March 31, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0f5c22881908044a178d670684c |
completed | March 31, 2026, 2:57 p.m. |
Created at: March 30, 2026, 5:16 p.m.