Triple
T18670887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 33rd Waffen Grenadier Division of the SS Charlemagne (1st French) |
E456470
|
entity |
| Predicate | languageSpokenByTroops |
P10179
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [33rd Waffen Grenadier Division of the SS Charlemagne (1st French), languageSpokenByTroops, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageSpokenByTroops Context triple: [33rd Waffen Grenadier Division of the SS Charlemagne (1st French), languageSpokenByTroops, French]
-
A.
militaryBranchLanguage
Indicates the language or languages officially used or primarily associated with a particular military branch.
-
B.
combatantLanguage
chosen
Indicates the language used by a combatant in a conflict or competitive interaction.
-
C.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
D.
languageGroupSpoken
Indicates that a particular language group is spoken or used for communication by an entity.
-
E.
militaryLanguage
Indicates that the communication or expression is conveyed using military-specific terminology, style, or jargon.
- 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e556b1140c81908002c27a33c03ae2 |
completed | April 19, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69e478db7a248190a8c6584673773923 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:48 a.m.