Triple
T33815740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duncan |
E866667
|
entity |
| Predicate | fandomEffectOnRelationship |
P177735
|
FINISHED |
| Object | causes strain |
—
|
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: causes strain | Statement: [Duncan, fandomEffectOnRelationship, causes strain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fandomEffectOnRelationship Context triple: [Duncan, fandomEffectOnRelationship, causes strain]
-
A.
fandomReception
Indicates how a work, character, or creator is perceived, evaluated, and responded to by its fan community.
-
B.
fandomContext
Indicates that the relationship or action occurs specifically within the context of a particular fandom or fan community.
-
C.
fandomUses
Indicates that a fandom makes use of, relies on, or incorporates a particular resource, tool, platform, or element.
-
D.
fandomScope
Indicates the extent or boundaries of a fandom-related relationship, such as how broadly or narrowly a fan’s interest, participation, or recognition applies.
-
E.
fandomFocus
Indicates that one entity is primarily centered on, dedicated to, or concerned with the fan community or fan-related aspects of another entity.
- 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_69f349911a8c81908478662194b23d8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7009d39508190af7301f824615e88 |
completed | May 3, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
| PDg | Predicate description generation | batch_69f6ffb7554881908993d6d2ffbcf8f5 |
completed | May 3, 2026, 7:56 a.m. |
Created at: May 1, 2026, 1:46 a.m.