Triple
T34400408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Canada (2029) |
E882961
|
entity |
| Predicate | hasLengthOverall |
P140284
|
FINISHED |
| Object | to be determined |
—
|
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: to be determined | Statement: [SS Empress of Canada (2029), hasLengthOverall, to be determined]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLengthOverall Context triple: [SS Empress of Canada (2029), hasLengthOverall, to be determined]
-
A.
hasCaseLength
Indicates that an entity is associated with a specific duration or length of a case (e.g., legal, medical, or procedural case).
-
B.
hasTotalNumber
Indicates that an entity is associated with a specific overall count or sum of items, elements, or units.
-
C.
commonTotalLength
Indicates that the entities share the same overall measured length.
-
D.
totalLength_m
chosen
Indicates the overall measured length of something expressed in meters.
-
E.
hasDegreeLength
Indicates that something possesses a length measured in degrees, typically expressing angular extent or size.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fde49a084081909d99b1e0258169d5 |
completed | May 8, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69fde1d04bd881909a46ecbbf18dfe59 |
completed | May 8, 2026, 1:14 p.m. |
Created at: May 1, 2026, 1:59 a.m.