Triple
T31001168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jesse (TV series) |
E789940
|
entity |
| Predicate | mainCharacterWorkplace |
P93741
|
FINISHED |
| Object | German-themed bar |
—
|
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: German-themed bar | Statement: [Jesse (TV series), mainCharacterWorkplace, German-themed bar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterWorkplace Context triple: [Jesse (TV series), mainCharacterWorkplace, German-themed bar]
-
A.
mainCharacterWorkplaceType
Indicates the type or kind of workplace where the main character is employed or primarily works.
-
B.
locationOfWork
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
C.
protagonistEmployerLocation
Indicates the location where the protagonist’s employer is based or operates.
-
D.
workAt
chosen
Indicates that an entity is employed by or performs work for a particular organization, company, or place.
-
E.
locationInWork
Indicates that one entity specifies the place or setting where another entity occurs, is situated, or takes place within a particular work (e.g., a scene’s location in a film or a chapter’s setting in a book).
- 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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 29, 2026, 8:56 p.m.