Triple
T25083418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arevmtyan Hayeren |
E628245
|
entity |
| Predicate | glossonymType |
P105156
|
FINISHED |
| Object | endonym |
—
|
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: endonym | Statement: [Arevmtyan Hayeren, glossonymType, endonym]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: glossonymType Context triple: [Arevmtyan Hayeren, glossonymType, endonym]
-
A.
hasGlossonym
chosen
Indicates a relationship where an entity is associated with the specific name or term used to refer to a language (its glossonym).
-
B.
etymologyGloss
Indicates that a term’s meaning is explained by a brief gloss specifically describing its etymological origin or source.
-
C.
meaningGloss
Indicates that the predicate provides a brief explanatory phrase or paraphrase capturing the meaning or sense of another expression or item.
-
D.
heteronymOf
Indicates that two words share the same spelling but differ in pronunciation and meaning.
-
E.
hasMultilingualGlosses
Indicates that an entity is associated with glosses or explanatory labels available in multiple languages.
- 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_69e2ff2e73f881909992bf3eda5c25cb |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f461e18c288190a0d06a7756fed024 |
completed | May 1, 2026, 8:18 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:22 a.m.