Triple
T12355684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German War Cemetery Sandweiler |
E294606
|
entity |
| Predicate | warDeadNationality |
P84069
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [German War Cemetery Sandweiler, warDeadNationality, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: warDeadNationality Context triple: [German War Cemetery Sandweiler, warDeadNationality, German]
-
A.
nationalityAtDeath
Indicates the country or national affiliation a person held at the time of their death.
-
B.
diedInConflict
Indicates that an entity lost their life as a direct result of a specific conflict or war.
-
C.
countryDuringWar
Indicates that a country exists or participates as a relevant actor during a specified war or armed conflict.
-
D.
casualtiesCountry
chosen
Indicates that the specified country is the one in which the recorded casualties (deaths or injuries) occurred or to which those casualties belong.
-
E.
countryOfDeath
Indicates the country in which an entity (typically a person) died.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.