Triple
T31597388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 4th Battalion, Royal 22e Régiment |
E806253
|
entity |
| Predicate | nativeLanguageOfPersonnel |
P151
|
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: [4th Battalion, Royal 22e Régiment, nativeLanguageOfPersonnel, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nativeLanguageOfPersonnel Context triple: [4th Battalion, Royal 22e Régiment, nativeLanguageOfPersonnel, French]
-
A.
nativeLanguage
chosen
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
B.
nationalLanguageSpoken
Indicates that a particular language is officially recognized and commonly used as a national language within a given country or region.
-
C.
languageOfCountryOfCitizenship
Indicates the language associated with the country where an entity holds citizenship.
-
D.
languageOfCitizenship
Indicates the language officially associated with or required for a given citizenship.
-
E.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
- 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_69f348d54ccc8190a03b5df9a2b40b25 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6abaa1f648190b77073771df3bf3b |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 10:31 p.m.