Triple
T14580613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese aircraft carrier Shinano |
E342181
|
entity |
| Predicate | voyageStatusAtSinking |
P114938
|
FINISHED |
| Object | maiden voyage |
—
|
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: maiden voyage | Statement: [Japanese aircraft carrier Shinano, voyageStatusAtSinking, maiden voyage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voyageStatusAtSinking Context triple: [Japanese aircraft carrier Shinano, voyageStatusAtSinking, maiden voyage]
-
A.
legalStatusAtTimeOfSinking
Indicates the legal status or condition that applied to an entity at the specific time it sank.
-
B.
constructionStatusAtSinking
Indicates the stage or condition of a structure’s construction at the time it sank.
-
C.
missionAtTimeOfSinking
Indicates that a vessel was engaged in a specific mission or operational role at the time it sank.
-
D.
placeOfSinking
Indicates the location where an object or entity sank or was submerged.
-
E.
wreckStatus
Indicates the condition or state of damage of an object, typically describing whether and how badly it has been wrecked.
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f6f78c81908a30ecb4c025299d |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:24 a.m.