Triple
T26342841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wizard's rule of Oz |
E662695
|
entity |
| Predicate | hasFictionalSuccessor |
P180120
|
FINISHED |
| Object | Princess Ozma's benevolent rule |
—
|
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: Princess Ozma's benevolent rule | Statement: [Wizard's rule of Oz, hasFictionalSuccessor, Princess Ozma's benevolent rule]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSuccessor Context triple: [Wizard's rule of Oz, hasFictionalSuccessor, Princess Ozma's benevolent rule]
-
A.
hasSequelInCanon
Indicates that a work has a subsequent work that continues its story within the officially recognized continuity.
-
B.
hasSequel
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
-
C.
hasSequelDepiction
Indicates that one depiction of something is followed by another depiction that continues its story or sequence.
-
D.
hasSequelOrRelated
Indicates that one work follows, continues, or is otherwise narratively or thematically related to another work.
-
E.
hasSequelType
Indicates that one work has a sequel of a specified type or category in relation to another work.
- 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_69ee81304194819092e20e0fae3aee07 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
| PDg | Predicate description generation | batch_69f73221eef88190bd8905e6e9f5a586 |
completed | May 3, 2026, 11:31 a.m. |
Created at: April 26, 2026, 10:40 p.m.