Triple
T3403197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margarita Isabel |
E71703
|
entity |
| Predicate | hasNotableWorkType |
P26054
|
FINISHED |
| Object | film |
—
|
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: film | Statement: [Margarita Isabel, hasNotableWorkType, film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableWorkType Context triple: [Margarita Isabel, hasNotableWorkType, film]
-
A.
hasNotableWorkSetThere
Indicates that a notable work (such as a book, film, or other creative piece) is set in or takes place within the referenced location.
-
B.
hasWrittenWorkType
Indicates that an entity (typically a written work) is associated with a specific type or category of written work (such as novel, article, report, etc.).
-
C.
hasNotablePublicationType
Indicates that an entity is associated with a publication of a specific notable type or category.
-
D.
hasNotableMusicWork
Indicates that an entity is associated with a significant or well-known musical work, such as a composition, recording, or performance.
-
E.
notableTypeOfWork
chosen
Indicates that a work is a significant or defining example within a particular type or category of work associated with an entity.
- 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_69ad85aac4808190a092c9cc8911f584 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb8e78ec8819089417666dc29f412 |
completed | March 8, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69adadfa73ac8190a163f93e88d217f8 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.