Triple
T23741328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jarawan Bantu languages |
E586679
|
entity |
| Predicate | areRelevantTo |
P37
|
FINISHED |
| Object | reconstruction of Bantu language history |
—
|
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: reconstruction of Bantu language history | Statement: [Jarawan Bantu languages, areRelevantTo, reconstruction of Bantu language history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areRelevantTo Context triple: [Jarawan Bantu languages, areRelevantTo, reconstruction of Bantu language history]
-
A.
relevantToInstitution
Indicates that something has a meaningful connection, applicability, or significance to a particular institution.
-
B.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
hasLegalRelevanceIn
Indicates that something is legally significant, applicable, or has consequences within a specified legal context, case, or jurisdiction.
-
D.
mayRelateTo
Indicates a possible, but not certain, relationship or association between two entities.
-
E.
moreCloselyRelatedTo
Indicates that one entity has a stronger or closer relationship, connection, or similarity to a second entity than to some other reference entity.
- 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_69e24908efb08190bf755c3a9b91f222 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bad61d908190a0a8493bbba95d49 |
completed | April 29, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:11 p.m.