Triple
T37811734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brown Shipbuilding Company |
E942662
|
entity |
| Predicate | typeOfShipBuilt |
P51721
|
FINISHED |
| Object | destroyer escort |
—
|
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: destroyer escort | Statement: [Brown Shipbuilding Company, typeOfShipBuilt, destroyer escort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfShipBuilt Context triple: [Brown Shipbuilding Company, typeOfShipBuilt, destroyer escort]
-
A.
shipTypeProduced
chosen
Indicates that a particular type of ship is produced, built, or manufactured by a given entity.
-
B.
shipbuilderType
Indicates the specific kind or category of shipbuilder associated with an entity (e.g., by role, specialization, or organizational type).
-
C.
originalShipType
Indicates the type or category of ship that an entity was originally classified or built as.
-
D.
shipbuilder
Indicates that one entity is the builder or constructor of a ship associated with another entity.
-
E.
shipClass
Indicates the classification or type category to which a particular ship belongs.
- 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_69f76ee8104c8190ab17133ccd8f86e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.