Triple
T28904509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Charrington |
E733036
|
entity |
| Predicate | rentsRoomTo |
P161038
|
FINISHED |
| Object | Winston Smith |
—
|
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: Winston Smith | Statement: [Mr. Charrington, rentsRoomTo, Winston Smith]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rentsRoomTo Context triple: [Mr. Charrington, rentsRoomTo, Winston Smith]
-
A.
sharesRoomWith
Indicates that two entities occupy or use the same room at the same time.
-
B.
tenantOccupation
chosen
Indicates that an entity occupies or uses a property or premises as a tenant under a rental or lease arrangement.
-
C.
alsoTenant
Indicates that two or more entities share the status of being tenants, typically occupying the same property or rental arrangement.
-
D.
alsoTenantTo
Indicates that one entity is also a tenant of the same property or landlord as another entity, in addition to any other existing relationships.
-
E.
rentalModel
Indicates that one entity is used or provided to another under a specific rental arrangement, defining how the rental relationship is structured or operates.
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65ad948748190abe57197575a19dc |
completed | May 2, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69f6576487e081908d802f1caf59c423 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 8:05 a.m.