Triple
T2051302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Buck (DD-420) |
E45573
|
entity |
| Predicate | crewCasualtiesWhenSunk |
P33471
|
FINISHED |
| Object | over 150 killed |
—
|
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 150 killed | Statement: [USS Buck (DD-420), crewCasualtiesWhenSunk, over 150 killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewCasualtiesWhenSunk Context triple: [USS Buck (DD-420), crewCasualtiesWhenSunk, over 150 killed]
-
A.
fatalitiesOnboard
chosen
Indicates that the relationship specifies the number of people who died among those present on a particular vehicle or craft.
-
B.
shipsSunkOrTotalLoss
Indicates that the referenced ships were sunk or otherwise rendered a total loss (permanently unusable).
-
C.
sunkBy
Indicates that one entity (typically a vessel or structure) was caused to sink or be destroyed in water by another entity.
-
D.
sunkDuring
Indicates that one entity was sunk in the course of, or as a result of, the event or time period represented by another entity.
-
E.
casualtiesJapan
Indicates that an event or action resulted in casualties (deaths and/or injuries) occurring in Japan.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb98f5f4881908d9aa0f10be44041 |
completed | March 7, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_69abb7abba508190b872f345d3ba51bb |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:39 p.m.