Triple
T24731165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Songhay |
E618290
|
entity |
| Predicate | notableLanguageContact |
P22730
|
FINISHED |
| Object | Tuareg Berber |
—
|
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: Tuareg Berber | Statement: [Northern Songhay, notableLanguageContact, Tuareg Berber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLanguageContact Context triple: [Northern Songhay, notableLanguageContact, Tuareg Berber]
-
A.
languageContactWith
chosen
Indicates a relationship where two or more languages come into contact through their speakers, leading to interaction and potential mutual influence.
-
B.
notableMemberLanguage
Indicates that the language is notably associated with or used by a prominent member of the referenced group or entity.
-
C.
hasContactWithLanguage
Indicates that an entity has some form of interaction, exposure, or engagement with a particular language.
-
D.
historicalLanguageContact
Indicates that two language communities have been in contact in the past in a way that allowed linguistic influence or exchange between them.
-
E.
primaryLanguageContact
Indicates that one language serves as the main or dominant medium of communication in a particular contact situation between language communities.
- 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 18, 2026, 4:02 a.m.