Triple
T16894802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Dompaire |
E424269
|
entity |
| Predicate | GermanUnitType |
P25051
|
FINISHED |
| Object | Panzer brigade |
—
|
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: Panzer brigade | Statement: [Battle of Dompaire, GermanUnitType, Panzer brigade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GermanUnitType Context triple: [Battle of Dompaire, GermanUnitType, Panzer brigade]
-
A.
germanUnit
chosen
Indicates that an entity is a military or organizational unit that belongs to, originates from, or is associated with Germany.
-
B.
GermanArmyGroup
Indicates that an entity is a specific army group belonging to or associated with the German military.
-
C.
GermanLoss
Indicates that Germany experiences a loss, defeat, or negative outcome in the specified context or event.
-
D.
germanCommander
Indicates that the subject serves as a military commander for German forces in relation to the object.
-
E.
isMostProducedGermanAFV
Indicates that the subject is the German armored fighting vehicle (AFV) with the highest production quantity compared to all other German AFVs.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8d6bfc88190b6b47b89c1135871 |
completed | April 18, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.