Triple
T4771714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairmont San Francisco Hotel |
E105941
|
entity |
| Predicate | hasBanquetFacilities |
P22897
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Fairmont San Francisco Hotel, hasBanquetFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBanquetFacilities Context triple: [Fairmont San Francisco Hotel, hasBanquetFacilities, yes]
-
A.
hasBackstageFacilities
Indicates that a venue or location provides backstage areas and related facilities for performers or staff.
-
B.
hasDiningFeature
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
-
C.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
D.
hasHospitalityComponent
chosen
Indicates that something includes, involves, or is associated with a hospitality-related element, service, or function.
-
E.
offersBuffet
Indicates that one entity provides a buffet-style service or meal option to another entity.
- 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd655e5dcc8190a932be9b1baaffb2 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.