Triple
T19340694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tremont House (Boston hotel) |
E483745
|
entity |
| Predicate | hasFloorPlanFeature |
P97094
|
FINISHED |
| Object | central rotunda |
—
|
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: central rotunda | Statement: [Tremont House (Boston hotel), hasFloorPlanFeature, central rotunda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloorPlanFeature Context triple: [Tremont House (Boston hotel), hasFloorPlanFeature, central rotunda]
-
A.
hasFloorPlanShape
Indicates that an entity has a specific geometric or structural configuration defining the shape of its floor plan.
-
B.
hasFloorFeature
chosen
Indicates that a floor possesses or includes a specific feature or characteristic.
-
C.
floorPlanType
Indicates the specific layout or configuration category that a floor plan belongs to (e.g., studio, 1-bedroom, open-plan).
-
D.
floorPlan
Indicates that one entity serves as the architectural layout or room arrangement blueprint for another entity (such as a building or space).
-
E.
hasFloor
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a structure.
- 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e61856c0948190a3166b3bf3810e43 |
completed | April 20, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 1:33 p.m.