Triple
T11221219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annabelle Wallis |
E265568
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object | Mia Form |
E724828
|
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: Mia Form | Statement: [Annabelle Wallis, playedCharacter, Mia Form]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mia Form Context triple: [Annabelle Wallis, playedCharacter, Mia Form]
-
A.
Mia Form
chosen
Mia Form is the central protagonist of the story featuring Annabelle, around whom the main plot and character development revolve.
-
B.
Mia X
Mia X is an American rapper from New Orleans known as one of the prominent female artists of Master P’s No Limit Records in the 1990s.
-
C.
Mia
Mia is a feminine given name used in many cultures, often as a short form of names like Maria or Amelia.
-
D.
Mia
Mia is a major fine art museum in Minneapolis, Minnesota, known for its extensive and diverse collection spanning thousands of years and cultures.
-
E.
Mia Michaels
Mia Michaels is an Emmy-winning American choreographer renowned for her emotionally powerful contemporary dance works on stage, television, and film.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8eb84c48190b4f3bede254afde2 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4977cab4481909c6b94ca07cd5e4a |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 8, 2026, 9:30 p.m.