Triple
T38691292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Carriage Driver |
E949269
|
entity |
| Predicate | characterInFictionalUniverse |
P133542
|
FINISHED |
| Object | Land of Oz |
—
|
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: Land of Oz | Statement: [The Carriage Driver, characterInFictionalUniverse, Land of Oz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInFictionalUniverse Context triple: [The Carriage Driver, characterInFictionalUniverse, Land of Oz]
-
A.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
B.
activeInFictionalUniverse
Indicates that an entity participates, operates, or has a role within a specified fictional universe or setting.
-
C.
characterInFilmSeries
Indicates that a character appears in or is part of the cast of a particular film series.
-
D.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
-
E.
inUniverseCharacter
chosen
Indicates that a character exists within, and is part of, the fictional universe or continuity defined by a particular work or franchise.
- 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_69f76efe16148190befd5dd59c3dfeaa |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a0027e4a59481909417b2531daaf480 |
completed | May 10, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_6a0026a42bc08190ad3322ce625a523a |
completed | May 10, 2026, 6:33 a.m. |
Created at: May 3, 2026, 4:33 p.m.