Triple
T36559477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (2024) |
E901789
|
entity |
| Predicate | hasNamingYear |
P200290
|
FINISHED |
| Object | 2024 |
—
|
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: 2024 | Statement: [SS Empress of Britain (2024), hasNamingYear, 2024]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamingYear Context triple: [SS Empress of Britain (2024), hasNamingYear, 2024]
-
A.
hasNaming
Indicates that one entity assigns, bears, or is associated with a specific name or designation provided by another entity.
-
B.
hasYearOfNamesakeEvent
Indicates the specific year in which the event that a namesake is based on or named after took place.
-
C.
hasTypeOfYear
Indicates that a given year is classified as belonging to a specific type or category of year (e.g., fiscal, academic, leap).
-
D.
nicknameOfYear
Indicates that a given nickname is used to refer to or characterize a particular year.
-
E.
namesakeServiceYear
Indicates the year in which a service, event, or entity occurred or was established that serves as the namesake for 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_69f76e634e9481908c9ba1b87ab87c26 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff7eb7189c81909a8f73fbc4c48e02 |
completed | May 9, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69ff7e54e11081908fb5ce10c5aa7b53 |
completed | May 9, 2026, 6:35 p.m. |
| PDg | Predicate description generation | batch_69ff7eb638c48190aeca7b85b9b698ab |
completed | May 9, 2026, 6:36 p.m. |
Created at: May 3, 2026, 4:11 p.m.