Triple
T36860956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (1985) |
E910933
|
entity |
| Predicate | carriesNameOf |
P186597
|
FINISHED |
| Object | SS Empress of Britain (1906) |
—
|
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: SS Empress of Britain (1906) | Statement: [SS Empress of Britain (1985), carriesNameOf, SS Empress of Britain (1906)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carriesNameOf Context triple: [SS Empress of Britain (1985), carriesNameOf, SS Empress of Britain (1906)]
-
A.
nameOf
Indicates that one entity is the name or designation of another entity.
-
B.
alsoCarries
Indicates that an entity, in addition to other items or responsibilities it has, carries another specified item or load as well.
-
C.
followsNameOf
Indicates that one entity’s name comes immediately after another entity’s name in a specified ordering or sequence.
-
D.
hasNameGivenTo
Indicates that one entity is the name that has been assigned or given to another entity.
-
E.
hasNameCharacteristic
Indicates that an entity possesses a specific quality or attribute related to its name.
- 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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:13 p.m.