Triple
T36559420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (1978) |
E901787
|
entity |
| Predicate | hasDiningRooms |
P177295
|
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: [SS Empress of Britain (1978), hasDiningRooms, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiningRooms Context triple: [SS Empress of Britain (1978), hasDiningRooms, yes]
-
A.
hasStateDiningRoom
Indicates that an entity includes or is associated with a formal dining room area within its premises.
-
B.
hasDiningComponent
chosen
Indicates that something includes or is associated with a dining-related part, feature, or function.
-
C.
hasDiningFeature
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
-
D.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
E.
hasDiningOptionType
Indicates that an entity offers or is associated with a specific type or category of dining option (e.g., dine-in, takeout, delivery).
- 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_69f76e634e9481908c9ba1b87ab87c26 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff64b957bc81908afbc5914234a8ea |
completed | May 9, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69ff6446593c81909173e296eea2590c |
completed | May 9, 2026, 4:43 p.m. |
Created at: May 3, 2026, 4:11 p.m.