Triple
T126385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italic languages |
E2559
|
entity |
| Predicate | linguisticFeature |
P6520
|
FINISHED |
| Object | similar verbal morphology across subgroup |
—
|
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: similar verbal morphology across subgroup | Statement: [Italic languages, linguisticFeature, similar verbal morphology across subgroup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguisticFeature Context triple: [Italic languages, linguisticFeature, similar verbal morphology across subgroup]
-
A.
hasPhonemicContrast
Indicates that two or more speech sounds are distinguished in a language by differences that change word meaning.
-
B.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
C.
languageFamily
Indicates that two or more languages belong to the same genealogical language family or linguistic lineage.
-
D.
grammaticalStructure
Indicates the way linguistic elements are organized and related within a sentence or phrase according to grammatical rules.
-
E.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
- 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_69a251b54ea88190b18281669f59b4c0 |
completed | Feb. 28, 2026, 2:23 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564c11208190ad25495609d94d87 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2575d8a648190ad8e10d4b04e5e07 |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:27 a.m.