Triple
T30108623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harari Region |
E765198
|
entity |
| Predicate | languageFamilyOfHarari |
P35117
|
FINISHED |
| Object | Ethiosemitic languages |
—
|
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: Ethiosemitic languages | Statement: [Harari Region, languageFamilyOfHarari, Ethiosemitic languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageFamilyOfHarari Context triple: [Harari Region, languageFamilyOfHarari, Ethiosemitic languages]
-
A.
basedOnLanguageFamily
Indicates that one entity is derived from, structured according to, or otherwise determined by the language family to which another entity belongs.
-
B.
languageFamily
Indicates that two or more languages belong to the same genealogical language family or linguistic lineage.
-
C.
languageFamilyOf
chosen
Indicates that one entity is the language family to which the other entity (a specific language) belongs.
-
D.
languageFamilyHypotheses
Indicates proposed or theorized genealogical relationships among languages, grouping them into potential common families or macro-families.
-
E.
languageFamilyBranchOf
Indicates that one language family branch is a sub-group or subdivision within a larger language family.
- 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_69f22475ad7c8190be7f9541044a0bbb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fef3ceef648190b58027c93d757438 |
completed | May 9, 2026, 8:43 a.m. |
| PD | Predicate disambiguation | batch_69fef359da2c819091a034387b08821f |
completed | May 9, 2026, 8:42 a.m. |
Created at: April 29, 2026, 7:10 p.m.