Triple
T7752425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isuzu (damaged and later scuttled) |
E175799
|
entity |
| Predicate | scuttlingReason |
P17168
|
FINISHED |
| Object | damage sustained in battle |
—
|
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: damage sustained in battle | Statement: [Isuzu (damaged and later scuttled), scuttlingReason, damage sustained in battle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scuttlingReason Context triple: [Isuzu (damaged and later scuttled), scuttlingReason, damage sustained in battle]
-
A.
reasonForScuttling
chosen
Indicates the specific cause or motivation that led to a vessel being deliberately scuttled.
-
B.
sunkBy
Indicates that one entity (typically a vessel or structure) was caused to sink or be destroyed in water by another entity.
-
C.
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.
-
D.
fleetDestroyedBy
Indicates that a fleet was destroyed as a direct result of actions taken by another specified entity.
-
E.
missionAtTimeOfSinking
Indicates that a vessel was engaged in a specific mission or operational role at the time it sank.
- 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_69c6996180088190832e38e8d83ff54a |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c705257ca08190a78c592a1e616da8 |
completed | March 27, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69c7016df2b08190b2330a2010691431 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:08 p.m.