Triple
T29096685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mon Signor Hotel |
E735023
|
entity |
| Predicate | hasMainStaffCharacter |
P61558
|
FINISHED |
| Object | Ted the Bellhop |
—
|
NE NERFINISHED |
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: Ted the Bellhop | Statement: [Mon Signor Hotel, hasMainStaffCharacter, Ted the Bellhop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainStaffCharacter Context triple: [Mon Signor Hotel, hasMainStaffCharacter, Ted the Bellhop]
-
A.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
B.
hasMainThemeCharacter
Indicates that a work (such as a story, film, or game) features a specific character as its central or primary thematic focus.
-
C.
hasFictionalStaffMember
chosen
Indicates that an entity includes or employs a staff member who is a fictional character.
-
D.
mainCharactersAre
Indicates that the specified entities serve as the primary or central characters in a narrative or work.
-
E.
hasPrimaryCharacter
Indicates that an entity features another entity as its main or central character.
- 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69ff14d596e88190be5263b7f96a96cd |
completed | May 9, 2026, 11:04 a.m. |
| PD | Predicate disambiguation | batch_69ff13f0208081909369aeb3b77a6b1f |
completed | May 9, 2026, 11:01 a.m. |
Created at: April 28, 2026, 11:09 a.m.