Triple
T36699601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (1981) |
E906187
|
entity |
| Predicate | namingSeries |
P186173
|
FINISHED |
| Object | Empress ships |
—
|
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: Empress ships | Statement: [SS Empress of Britain (1981), namingSeries, Empress ships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namingSeries Context triple: [SS Empress of Britain (1981), namingSeries, Empress ships]
-
A.
designationSeries
Indicates that one designation belongs to or is part of a broader series of related designations.
-
B.
namingStructure
Indicates a relationship where one entity defines, organizes, or constrains the naming or label format used for another entity.
-
C.
typeDesignationSeries
Indicates that one entity serves as the formal type designation series (the reference series) for another entity in a classification or naming system.
-
D.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
E.
hasSeriesNumber
Indicates that an entity is assigned a specific ordinal or sequence number within a series or ordered set.
- 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_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c83f5960819089610ed39c839678 |
completed | May 3, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
| PDg | Predicate description generation | batch_69f7c776b4088190bef550c869da530d |
completed | May 3, 2026, 10:08 p.m. |
Created at: May 3, 2026, 4:12 p.m.