Triple
T21510775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blanche Hudson |
E530711
|
entity |
| Predicate | characterStatusAtStartOfFilm |
P131402
|
FINISHED |
| Object | retired film star |
—
|
LITERAL 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: retired film star | Statement: [Blanche Hudson, characterStatusAtStartOfFilm, retired film star]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterStatusAtStartOfFilm Context triple: [Blanche Hudson, characterStatusAtStartOfFilm, retired film star]
-
A.
statusAtStartOfFilm
chosen
Indicates the condition or situation an entity is in at the beginning of the film.
-
B.
legalStatusAtStartOfFilm
Indicates the legal condition or standing an entity has at the beginning of the film’s narrative.
-
C.
statusAtEndOfFilm
Indicates the condition or situation an entity is in when the film concludes.
-
D.
statusInFirstFilm
Indicates the role, condition, or situation an entity has in its first film appearance.
-
E.
protagonistStatusAtStart
Indicates the role or condition the main character is in at the beginning of the narrative or event.
- F. None of above.
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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea863b18819080e3ff249b10ec28 |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:25 p.m.