Triple
T35034635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Golden Fang |
E1010875
|
entity |
| Predicate | possiblyFictionalWithinWork |
P182895
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Golden Fang, possiblyFictionalWithinWork, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possiblyFictionalWithinWork Context triple: [The Golden Fang, possiblyFictionalWithinWork, true]
-
A.
isFictionalWorkWithinWork
Indicates that one fictional work is contained or presented as a subordinate or embedded work within another fictional work.
-
B.
isForFictionalWork
Indicates that something is intended to be used in, associated with, or specifically created for a fictional work.
-
C.
worksInFictionalContext
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
-
D.
usedInFictionalWork
Indicates that something (such as a concept, object, or character) appears or is employed within a specific fictional work.
-
E.
worksUnderInFiction
Indicates that, within a fictional context or narrative, one character or entity is hierarchically subordinate to and takes direction from another.
- F. None of above. chosen
Provenance (4 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_69f76dcea02c81908542a223f6d5059f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f794f24e588190965e39b77534d53f |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: May 3, 2026, 4:01 p.m.