Triple
T34357238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (2010) |
E881766
|
entity |
| Predicate | hasInServiceYear |
P187429
|
FINISHED |
| Object | 2010 |
—
|
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: 2010 | Statement: [SS Empress of Britain (2010), hasInServiceYear, 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInServiceYear Context triple: [SS Empress of Britain (2010), hasInServiceYear, 2010]
-
A.
enteredFullServiceYear
chosen
Indicates the year in which an entity began operating at its full, regular level of service.
-
B.
hasPlannedEntryIntoServiceYear
Indicates the year in which an entity is scheduled or planned to begin being in service or operational use.
-
C.
hasTimePeriodOfService
Indicates that an entity is associated with a specific span of time during which it provided service or was actively serving.
-
D.
hasPartInYear
Indicates that something includes or contains a specific part, component, or segment that is associated with a particular year.
-
E.
serviceNumberOrYearsOfService
Indicates a relationship that specifies either an entity’s service identification number or the duration of time the entity has served.
- 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_69f349bd06008190904c2f86c42749e3 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a002249ee388190a9501ee7630dc658 |
completed | May 10, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_6a002189273881909b6b687e2d61f5b1 |
completed | May 10, 2026, 6:11 a.m. |
Created at: May 1, 2026, 1:58 a.m.