Triple
T26167171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bois Belleau (R97) |
E654285
|
entity |
| Predicate | previousShipClass |
P179996
|
FINISHED |
| Object | Independence-class aircraft carrier |
—
|
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: Independence-class aircraft carrier | Statement: [Bois Belleau (R97), previousShipClass, Independence-class aircraft carrier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousShipClass Context triple: [Bois Belleau (R97), previousShipClass, Independence-class aircraft carrier]
-
A.
shipClass
Indicates the classification or type category to which a particular ship belongs.
-
B.
originalShipType
Indicates the type or category of ship that an entity was originally classified or built as.
-
C.
laterShipType
Indicates that one ship type chronologically succeeds or is introduced after another ship type.
-
D.
shipClassDeveloped
Indicates that a particular ship class was developed or designed by a specified entity (such as a country, organization, or manufacturer).
-
E.
firstShip
Indicates that the subject is the earliest or initial ship associated with, created by, or used in relation to the object.
- 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_69ee5b44391c81908bdbd8813ba9aa99 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_69f730890a008190a882f7828f1c9162 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 26, 2026, 8:33 p.m.