Triple
T210000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proto-Celtic |
E4692
|
entity |
| Predicate | hasLexicalInfluenceOn |
P9129
|
FINISHED |
| Object | toponymy in Europe |
—
|
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: toponymy in Europe | Statement: [Proto-Celtic, hasLexicalInfluenceOn, toponymy in Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLexicalInfluenceOn Context triple: [Proto-Celtic, hasLexicalInfluenceOn, toponymy in Europe]
-
A.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another language.
-
B.
hasCommonLoanwordsFrom
Indicates that two languages share loanwords that originate from the same source language.
-
C.
hasLinguisticFeature
Indicates that an entity possesses a particular linguistic property, trait, or characteristic.
-
D.
hasLinguisticElement
Indicates that one entity includes, is associated with, or is characterized by a particular linguistic component such as a word, phrase, symbol, or other language element.
-
E.
hasCognate
Indicates that two linguistic forms in different languages share a common historical origin, typically descending from the same ancestral word.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b4f71b88190866c8262922ae204 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25d3463648190ac716d7475378536 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.