Triple
T35849169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aethiopia |
E1036299
|
entity |
| Predicate | languageOfEtymology |
P506
|
FINISHED |
| Object | Ancient Greek |
—
|
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: Ancient Greek | Statement: [Aethiopia, languageOfEtymology, Ancient Greek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfEtymology Context triple: [Aethiopia, languageOfEtymology, Ancient Greek]
-
A.
etymologicalLanguage
chosen
Indicates the language from which a word or term is historically derived in its etymology.
-
B.
hasEtymologyConcept
Indicates that something derives its origin, form, or meaning from a particular etymological concept or source.
-
C.
etymologicalLanguageFamily
Indicates that one entity is the language family from which the other entity is etymologically derived or historically originates.
-
D.
etymologyStatus
Indicates the status or reliability classification of an etymological explanation for a term or name.
-
E.
hasLatinEtymology
Indicates that something originates from or is derived from a Latin word or linguistic root.
- 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_69f76e1a29e8819088280f26096aeb55 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00d08e8fac8190b59359134e6e1c03 |
completed | May 10, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_6a00d0127c088190a6f5b360450af113 |
completed | May 10, 2026, 6:36 p.m. |
Created at: May 3, 2026, 4:06 p.m.