Triple
T19832725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | katabasis |
E476502
|
entity |
| Predicate | hasStructuralRole |
P118631
|
FINISHED |
| Object | central episode in a quest narrative |
—
|
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: central episode in a quest narrative | Statement: [katabasis, hasStructuralRole, central episode in a quest narrative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStructuralRole Context triple: [katabasis, hasStructuralRole, central episode in a quest narrative]
-
A.
hasStructureRole
chosen
Indicates that an entity serves a specific functional or positional role within a larger structure or organizational arrangement.
-
B.
hasSectionRole
Indicates that an entity holds a specific role or function within a particular section or subdivision of a larger structure or context.
-
C.
haveStructure
Indicates that an entity possesses a particular internal organization, arrangement, or structural composition.
-
D.
hasStructuralStyle
Indicates that one entity possesses, exhibits, or is characterized by a particular architectural or structural design style.
-
E.
hasEarlyScreenRole
Indicates that an entity played a role in an early stage of another entity’s screen-based career or production history.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656cf7e488190b4be28b5e7b363bf |
completed | April 20, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.