Triple
T12941134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japhy Ryder |
E309638
|
entity |
| Predicate | influencedByInFiction |
P92229
|
FINISHED |
| Object | Chinese poetry |
—
|
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: Chinese poetry | Statement: [Japhy Ryder, influencedByInFiction, Chinese poetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedByInFiction Context triple: [Japhy Ryder, influencedByInFiction, Chinese poetry]
-
A.
basedOnInFiction
chosen
Indicates that a fictional work, character, or element is derived from, inspired by, or modeled after another real or fictional source.
-
B.
usedInFictionalWork
Indicates that something (such as a concept, object, or character) appears or is employed within a specific fictional work.
-
C.
relatedToInFiction
Indicates that one entity is connected to another within a fictional context, such as a story, universe, or narrative work.
-
D.
hasPlaceInFiction
Indicates that a fictional work or element is associated with, set in, or takes place within a particular fictional location or setting.
-
E.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:43 p.m.