Triple
T14044674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Body of Proof |
E337926
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Megan Hunt |
E444918
|
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: Megan Hunt | Statement: [Body of Proof, mainCharacter, Megan Hunt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Megan Hunt Context triple: [Body of Proof, mainCharacter, Megan Hunt]
-
A.
Megan Hunt
chosen
Megan Hunt is the brilliant but emotionally complex medical examiner protagonist of the television series "Body of Proof."
-
B.
Megan Morgan
Megan Morgan is a character from the 1988 sci-fi horror comedy film "Critters 2: The Main Course."
-
C.
Megan Howell
Megan Howell is a person notable enough to be specifically referenced by name, though no widely recognized public information about her is provided in this context.
-
D.
Megan Burns
Megan Burns is a British actress best known for her role as Hannah in the post-apocalyptic horror film "28 Days Later."
-
E.
Megan Foster
Megan Foster is an American local government leader serving as the mayor of Coralville, Iowa.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de312b94308190bd0961f5bc719c7b |
completed | April 14, 2026, 12:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef5c11708190a7fd4c0682b6ed81 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 9, 2026, 10:20 p.m.