Triple
T4819252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blair House |
E107667
|
entity |
| Predicate | hasBedrooms |
P16000
|
FINISHED |
| Object | over 100 rooms including guest suites |
—
|
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: over 100 rooms including guest suites | Statement: [Blair House, hasBedrooms, over 100 rooms including guest suites]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBedrooms Context triple: [Blair House, hasBedrooms, over 100 rooms including guest suites]
-
A.
numberOfBedrooms
chosen
Indicates the quantity of bedrooms associated with a given property or dwelling.
-
B.
bedCount
Indicates the number of beds associated with an entity, such as a room, facility, or accommodation.
-
C.
hasBedType
Indicates that an entity (such as a room or accommodation) is associated with a specific type or configuration of bed.
-
D.
numberOfBathrooms
Indicates the total count of bathrooms associated with an entity (such as a property or unit).
-
E.
beds
Indicates that one entity provides or designates a place for another entity to sleep or rest.
- 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.