Triple
T11719471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michif |
E278587
|
entity |
| Predicate | hasNounSystemFrom |
P100969
|
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: [Michif, hasNounSystemFrom, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNounSystemFrom Context triple: [Michif, hasNounSystemFrom, French]
-
A.
hasNounClassSystem
Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the language.
-
B.
hasPronounSystem
Indicates that an entity possesses or employs a particular system or set of rules for using pronouns.
-
C.
hasNounDeclensionType
Indicates that a noun is associated with a specific grammatical declension pattern or type.
-
D.
hasNounEnding
Indicates that something possesses or exhibits a particular noun-forming ending or suffix.
-
E.
hasNounIncorporation
Indicates that a verb incorporates a noun root or stem into its own form, forming a single complex predicate that expresses both the action and its nominal participant.
- F. None of above. chosen
Provenance (4 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4c26e4c8190ae30d906b4fd4221 |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7d483081909c2a101087515d74 |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:40 p.m.