Triple
T37166422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German submarine U-557 |
E920807
|
entity |
| Predicate | victimOfFriendlyFire |
P177410
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [German submarine U-557, victimOfFriendlyFire, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimOfFriendlyFire Context triple: [German submarine U-557, victimOfFriendlyFire, true]
-
A.
victimDiedIn
Indicates that the victim lost their life as a result of, or during the course of, the referenced event or circumstance.
-
B.
victimSide
Indicates that one entity is on, represents, or corresponds to the side of the victim in a conflict, incident, or harmful event.
-
C.
killedInAttack
Indicates that an entity died as a direct result of a specific attack event.
-
D.
victimArmedStatus
Indicates whether the victim involved in an incident was armed, and if so, with what type of weapon or object.
-
E.
victimWas
chosen
Indicates that one entity was the victim of an action, event, or harmful behavior carried out by another entity.
- 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_69f76ea0429081908c711b55599eac3c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.