Triple
T14286264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petronella Osgood |
E354183
|
entity |
| Predicate | fandomTrait |
P96545
|
FINISHED |
| Object | Doctor fangirl |
—
|
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: Doctor fangirl | Statement: [Petronella Osgood, fandomTrait, Doctor fangirl]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fandomTrait Context triple: [Petronella Osgood, fandomTrait, Doctor fangirl]
-
A.
fandomCharacteristic
chosen
Indicates that an entity possesses a particular trait, behavior, or quality specifically in the context of its fandom or fan community.
-
B.
fandomType
Indicates the specific category or kind of fandom relationship that exists between an entity and the subject of that fandom.
-
C.
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.
-
D.
fandomIdentity
Indicates that an entity identifies as a fan or member of a particular fandom associated with another entity.
-
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.
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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de697ef40c8190bea37724b28c2e99 |
completed | April 14, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:11 a.m.