Triple
T36860991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Canada (1982) |
E910934
|
entity |
| Predicate | builtInShipyard |
P159340
|
FINISHED |
| Object | John Brown & Company shipyard |
—
|
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: John Brown & Company shipyard | Statement: [SS Empress of Canada (1982), builtInShipyard, John Brown & Company shipyard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: builtInShipyard Context triple: [SS Empress of Canada (1982), builtInShipyard, John Brown & Company shipyard]
-
A.
hasShipyardIn
Indicates that an entity operates or possesses a shipyard located in a specified place.
-
B.
hasShipyardType
Indicates the specific category or classification of shipyard associated with an entity.
-
C.
shipbuilder
chosen
Indicates that one entity is the builder or constructor of a ship associated with another entity.
-
D.
shipbuilderType
Indicates the specific kind or category of shipbuilder associated with an entity (e.g., by role, specialization, or organizational type).
-
E.
shipyard
Indicates a relationship where a location functions as a facility for building, repairing, or maintaining ships.
- 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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.