Triple
T5656440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bedtime |
E124629
|
entity |
| Predicate | fictionalUniverseScope |
P15645
|
FINISHED |
| Object | single suburban street |
—
|
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: single suburban street | Statement: [Bedtime, fictionalUniverseScope, single suburban street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalUniverseScope Context triple: [Bedtime, fictionalUniverseScope, single suburban street]
-
A.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
B.
portraysFictionalUniverse
Indicates that one entity depicts, represents, or presents the fictional universe in which another entity is set.
-
C.
fictionalUniverseCreated
Indicates that one entity is the creator or originator of a particular fictional universe or setting in which stories or works take place.
-
D.
hasFictionalUniverseElement
chosen
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
E.
hasFictionalUniverseGenre
Indicates that a fictional universe is associated with a particular genre that characterizes its overall style, themes, or narrative type.
- 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_69c0082774a481909d7e63fb2aad56ac |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c0236d3f94819095111c41a323612d |
completed | March 22, 2026, 5:14 p.m. |
| PD | Predicate disambiguation | batch_69c021ba4ec481909db8cdbf0e907dd6 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:42 p.m.