Triple
T448921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Nubia |
E7083
|
entity |
| Predicate | hasLanguageEvidenceOf |
P14924
|
FINISHED |
| Object | Egyptian language |
—
|
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: Egyptian language | Statement: [Lower Nubia, hasLanguageEvidenceOf, Egyptian language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageEvidenceOf Context triple: [Lower Nubia, hasLanguageEvidenceOf, Egyptian language]
-
A.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
B.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
C.
hasSignificantLanguage
Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
-
D.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
E.
hasLinguisticHeritage
Indicates that one entity possesses or is associated with the linguistic background, tradition, or ancestry of another entity.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef6755a08190a057e72279b70456 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2ede1a1108190a4a06b3416ae6156 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef611b9c8190ac5e9174744d9127 |
completed | Feb. 28, 2026, 1:36 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.