Triple
T30989031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Akron (ZRS-4) |
E789615
|
entity |
| Predicate | crewLostInWreck |
P33471
|
FINISHED |
| Object | over 70 |
—
|
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: over 70 | Statement: [USS Akron (ZRS-4), crewLostInWreck, over 70]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewLostInWreck Context triple: [USS Akron (ZRS-4), crewLostInWreck, over 70]
-
A.
crewComplementAtSinking
Indicates the number or composition of a vessel’s crew present on board at the time it sank.
-
B.
sankOnMaidenVoyage
Indicates that the subject vessel sank during its very first voyage.
-
C.
fatalitiesOnboard
chosen
Indicates that the relationship specifies the number of people who died among those present on a particular vehicle or craft.
-
D.
shipwreckEvent
Indicates an event in which a ship is destroyed, stranded, or severely damaged, typically resulting in loss or abandonment at sea or near a shoreline.
-
E.
lostToSea
Indicates that something has been carried away or disappeared into the sea, resulting in its loss.
- 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_69f224c550b081909ddfceb0c3d03bdd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:56 p.m.