Triple
T35801421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hostel: Part II |
E1034986
|
entity |
| Predicate | containsFictionalOrganization |
P202927
|
FINISHED |
| Object | Elite Hunting |
—
|
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: Elite Hunting | Statement: [Hostel: Part II, containsFictionalOrganization, Elite Hunting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsFictionalOrganization Context triple: [Hostel: Part II, containsFictionalOrganization, Elite Hunting]
-
A.
hasFictionalCorporation
Indicates that an entity is associated with or includes a fictional corporation within its content, setting, or narrative.
-
B.
worksForFictionalOrganization
Indicates that an entity is employed by or affiliated as a worker with a fictional organization.
-
C.
hasFictionalBusinessType
Indicates that an entity is associated with a type or category of fictional business it operates or represents.
-
D.
hasFictionalProductionCompany
Indicates that one entity is associated with or owns a production company that exists only within a fictional context.
-
E.
hasFictionalCompanyMethod
Indicates that an entity employs or is associated with a particular method, approach, or technique used by a fictional company.
- F. None of above. chosen
Provenance (4 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00d15f7b788190a3bf440be7837192 |
completed | May 10, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_6a00d0f8ef548190b1c15b06164eec4a |
completed | May 10, 2026, 6:39 p.m. |
| PDg | Predicate description generation | batch_6a00d15e82708190b1246937c695da7e |
completed | May 10, 2026, 6:41 p.m. |
Created at: May 3, 2026, 4:06 p.m.