Triple
T7223554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serer language |
E150319
|
entity |
| Predicate | sharesLoanwordsWith |
P2268
|
FINISHED |
| Object | Wolof 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: Wolof language | Statement: [Serer language, sharesLoanwordsWith, Wolof language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesLoanwordsWith Context triple: [Serer language, sharesLoanwordsWith, Wolof language]
-
A.
hasCommonLoanwordsFrom
chosen
Indicates that two languages share loanwords that originate from the same source language.
-
B.
sharesSpellingWith
Indicates that two entities have identical or substantially identical written forms (i.e., they are spelled the same way).
-
C.
sharesEtymologyWith
Indicates that two terms originate from the same linguistic root or source word, or have closely related historical word origins.
-
D.
sharesLexiconWith
Indicates that two entities use or are associated with the same set of lexical items, vocabulary, or word inventory.
-
E.
sharesLanguageWith
Indicates that two entities use at least one common language for communication.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e9b54a5c8190a4a289f32853a8fe |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e761b7fc8190857794d78af1b468 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:54 p.m.