Triple
T34400327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Canada (1964) |
E882959
|
entity |
| Predicate | christenedAs |
P179645
|
FINISHED |
| Object | Empress of Canada |
—
|
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: Empress of Canada | Statement: [SS Empress of Canada (1964), christenedAs, Empress of Canada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: christenedAs Context triple: [SS Empress of Canada (1964), christenedAs, Empress of Canada]
-
A.
christenedBy
Indicates that an entity received its name or was formally dedicated through a christening performed by another entity.
-
B.
christenedDate
Indicates the date on which something was formally named or dedicated, typically in a ceremonial context.
-
C.
coronatedNameAtBirth
Indicates that an entity’s coronation name is the same as their name at birth.
-
D.
usedAsNamesakeFor
Indicates that one entity serves as the source or inspiration for the name given to another entity.
-
E.
changedNameInHonorOf
Indicates that an entity altered its name specifically to honor or pay tribute to another entity.
- F. None of above. chosen
Provenance (4 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7238172748190b8cd340ad1f4ba80 |
completed | May 3, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
| PDg | Predicate description generation | batch_69f72349f1108190b6a06758ab2f40bb |
completed | May 3, 2026, 10:28 a.m. |
Created at: May 1, 2026, 1:59 a.m.