Triple
T2566799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperator |
E57368
|
entity |
| Predicate | cognateIn |
P2525
|
FINISHED |
| Object | English word "emperor" |
—
|
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: English word "emperor" | Statement: [Imperator, cognateIn, English word "emperor"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cognateIn Context triple: [Imperator, cognateIn, English word "emperor"]
-
A.
cognateOf
Indicates that two linguistic forms share a common historical origin, typically descending from the same ancestral word.
-
B.
cognate
Indicates that two linguistic forms share a common historical origin, typically deriving from the same ancestral word.
-
C.
hasCognate
chosen
Indicates that two linguistic forms in different languages share a common historical origin, typically descending from the same ancestral word.
-
D.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
E.
hasCommonLoanwordsFrom
Indicates that two languages share loanwords that originate from the same source language.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3602ed08190aad0f9c7ac577eb0 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0cc8d308190ae7aa32b8f5ae2e5 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.