Triple
T31252651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine McCormack as Greta Schröder |
E796870
|
entity |
| Predicate | realPersonDepicted |
P171500
|
FINISHED |
| Object | Greta Schröder |
—
|
NE NERFINISHED |
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: Greta Schröder | Statement: [Catherine McCormack as Greta Schröder, realPersonDepicted, Greta Schröder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realPersonDepicted Context triple: [Catherine McCormack as Greta Schröder, realPersonDepicted, Greta Schröder]
-
A.
realPerson
Indicates that the referenced entity corresponds to an actual human individual, as opposed to a fictional, anonymous, or non-human entity.
-
B.
namedIndividual
Indicates that the subject is a specific, uniquely identified individual entity rather than a general class or type.
-
C.
documentedPerson
Indicates that a person is the subject of documentation or records in some source or system.
-
D.
depictedPersonAlternativeName
Indicates that an alternative or variant name is used to refer to the person depicted.
-
E.
featuresRealPersonAsHimself
Indicates that a real person appears in the work portraying themself rather than a fictional character.
- F. None of above. chosen
Provenance (4 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 29, 2026, 9:12 p.m.