Triple
T5018711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzanne "Crazy Eyes" Warren |
E112796
|
entity |
| Predicate | hasFandomStatus |
P27257
|
FINISHED |
| Object | fan-favorite character |
—
|
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: fan-favorite character | Statement: [Suzanne "Crazy Eyes" Warren, hasFandomStatus, fan-favorite character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFandomStatus Context triple: [Suzanne "Crazy Eyes" Warren, hasFandomStatus, fan-favorite character]
-
A.
hasFanCommunity
Indicates that an entity is associated with a group of fans who actively follow, support, or engage around it.
-
B.
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.
-
C.
fandomFocus
Indicates that one entity is primarily centered on, dedicated to, or concerned with the fan community or fan-related aspects of another entity.
-
D.
hasFan
Indicates that an entity is the admirer, supporter, or enthusiast of another entity.
-
E.
fameStatus
chosen
Indicates the level or state of public recognition or renown associated with an 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73415e088190802f9bb283262386 |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.