Triple
T11584892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Tilde |
E274724
|
entity |
| Predicate | genreOfFictionalUniverse |
P31344
|
FINISHED |
| Object | spy fiction |
—
|
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: spy fiction | Statement: [Princess Tilde, genreOfFictionalUniverse, spy fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfFictionalUniverse Context triple: [Princess Tilde, genreOfFictionalUniverse, spy fiction]
-
A.
hasFictionalUniverseGenre
chosen
Indicates that a fictional universe is associated with a particular genre that characterizes its overall style, themes, or narrative type.
-
B.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
C.
hasFictionalUniverseProperty
Indicates that a fictional universe possesses a specific characteristic, attribute, or property.
-
D.
portraysFictionalUniverse
Indicates that one entity depicts, represents, or presents the fictional universe in which another entity is set.
-
E.
expandsFictionalUniverseOf
Indicates that one work adds new content, details, or dimensions to the fictional universe established by another work.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89462203881908870e991a5b21770 |
completed | April 10, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dcbacd0819094d4a1237055affa |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.