Triple
T1461443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wishing-Chair |
E31519
|
entity |
| Predicate | protagonistRelationship |
P27138
|
FINISHED |
| Object | siblings |
—
|
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: siblings | Statement: [The Wishing-Chair, protagonistRelationship, siblings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistRelationship Context triple: [The Wishing-Chair, protagonistRelationship, siblings]
-
A.
hasProtagonistRelationship
chosen
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
-
B.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
-
C.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
D.
protagonistBasedOn
Indicates that a fictional work’s main character is modeled on, inspired by, or derived from a particular real or fictional person or entity.
-
E.
protagonistAlterEgoOf
Indicates that one entity is the alternate identity or secret persona of the main character (protagonist) in a narrative.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c59ecb60819082217b034e18381f |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47ec5108190b1772237f2e5d90b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.