Triple
T21927555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eleventh Corps |
E541479
|
entity |
| Predicate | primaryLanguageOfManySoldiers |
P1252
|
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: [Eleventh Corps, primaryLanguageOfManySoldiers, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLanguageOfManySoldiers Context triple: [Eleventh Corps, primaryLanguageOfManySoldiers, German]
-
A.
combatantLanguage
Indicates the language used by a combatant in a conflict or competitive interaction.
-
B.
militaryBranchLanguage
Indicates the language or languages officially used or primarily associated with a particular military branch.
-
C.
languageOfMilitaryService
Indicates the language in which a person’s military service was conducted or officially recorded.
-
D.
primaryLanguageOf
chosen
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
E.
languageOfSurroundingCulture
Indicates that one entity is the language predominantly used or characteristic of the surrounding culture associated with 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_69e0c47d74488190a15119108794a307 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f123fc188481909c74fd5f1bd52258 |
completed | April 28, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:46 p.m.