Triple
T19165275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lima, Ohio |
E469161
|
entity |
| Predicate | fictionalRoleInWork |
P25662
|
FINISHED |
| Object | hometown setting of main characters in Glee |
—
|
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: hometown setting of main characters in Glee | Statement: [Lima, Ohio, fictionalRoleInWork, hometown setting of main characters in Glee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalRoleInWork Context triple: [Lima, Ohio, fictionalRoleInWork, hometown setting of main characters in Glee]
-
A.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
-
B.
fictionalUniverseRole
Indicates the role or function an entity has within a particular fictional universe or narrative setting.
-
C.
hasFictionalRole
chosen
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
D.
literaryRole
Indicates the specific narrative or functional role an entity holds within a literary work or text.
-
E.
fictionalOccupation
Indicates that one entity is the imaginary or narrative-based job, role, or profession attributed to another entity within a fictional context.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f15ee064819087f9fd822236298f |
completed | April 20, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b83d6881908e6271c620f74100 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.