Triple
T30414746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ARA Uruguay |
E773719
|
entity |
| Predicate | museumShipSince |
P52115
|
FINISHED |
| Object | late 1950s |
—
|
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: late 1950s | Statement: [ARA Uruguay, museumShipSince, late 1950s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: museumShipSince Context triple: [ARA Uruguay, museumShipSince, late 1950s]
-
A.
becameMuseumShip
Indicates that a vessel or ship was converted from active service into a museum exhibit open to the public.
-
B.
hasMuseumShip
Indicates that one entity possesses or is associated with a museum ship, typically a preserved vessel displayed for public exhibition.
-
C.
hasMaritimeMuseum
Indicates that one entity possesses, hosts, or includes a maritime museum as part of its features or facilities.
-
D.
inMuseumCollectionSince
chosen
Indicates the date or time from which an item has been part of a museum’s collection.
-
E.
openedAsMuseumIn
Indicates that a place or building began operating as a museum in a specified year or at a specified time.
- 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_69f22490b8b48190ab10c886a8d58c89 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68648b7908190871c0559199f1192 |
completed | May 2, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 8:05 p.m.