Triple
T36284864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (2019) |
E893048
|
entity |
| Predicate | hasNameSeries |
P200195
|
FINISHED |
| Object | Empress of Britain |
—
|
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 Britain | Statement: [SS Empress of Britain (2019), hasNameSeries, Empress of Britain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameSeries Context triple: [SS Empress of Britain (2019), hasNameSeries, Empress of Britain]
-
A.
hasNameGivenBy
Indicates that one entity has a name that was assigned or bestowed by another entity.
-
B.
hasNameInFamily
Indicates that an entity is known or referred to by a particular name within the context of a specific family or familial group.
-
C.
hasNameGivenTo
Indicates that one entity is the name that has been assigned or given to another entity.
-
D.
hasFamilyNameOf
Indicates that one entity bears or uses the same family name (surname) as another entity.
-
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_69f76e4955c08190b8cfddca34fc0242 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff79e7206c8190a809b5f2a6261378 |
completed | May 9, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69ff798356b881908645074fb3a96517 |
completed | May 9, 2026, 6:14 p.m. |
| PDg | Predicate description generation | batch_69ff79e645c08190a974b5239efac35b |
completed | May 9, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:09 p.m.