Triple
T38288577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyrus |
E1022289
|
entity |
| Predicate | linguisticAdaptation |
P108920
|
FINISHED |
| Object | Latin |
—
|
NE NERFINISHED |
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: Latin | Statement: [Cyrus, linguisticAdaptation, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguisticAdaptation Context triple: [Cyrus, linguisticAdaptation, Latin]
-
A.
linguisticAssimilation
Indicates the process by which one language or linguistic feature becomes more similar to or integrated with another through contact or influence.
-
B.
linguisticStrategy
Indicates the communicative approach or method used in language to achieve a particular interactional, rhetorical, or pragmatic goal.
-
C.
linguisticVariation
Indicates a relationship where one linguistic form differs from another in expression, usage, or structure while remaining related in meaning or function.
-
D.
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.
-
E.
linguisticInfluence
chosen
Indicates that one entity has affected, shaped, or contributed to the language, style, or linguistic features of another entity.
- 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_69f76df190f081908d5aa02c8a9286d0 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:30 p.m.