Triple
T14788807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denkyira |
E347597
|
entity |
| Predicate | hasEthnicDescendants |
P115409
|
FINISHED |
| Object | Denkyira people in modern Ghana |
—
|
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: Denkyira people in modern Ghana | Statement: [Denkyira, hasEthnicDescendants, Denkyira people in modern Ghana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthnicDescendants Context triple: [Denkyira, hasEthnicDescendants, Denkyira people in modern Ghana]
-
A.
hasEthnicCharacteristic
Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
-
B.
holderEthnicity
Indicates the ethnic background or group to which the holder of something (e.g., a document, account, or item) belongs.
-
C.
hasEthnicInfluence
Indicates that one entity has a cultural, traditional, or ethnic impact on, or contributes to shaping the ethnic character of, another entity.
-
D.
ethnicOrigin
Indicates the relationship where an entity is associated with a particular ethnic group or ancestry.
-
E.
hasEthnolinguisticPresence
chosen
Indicates that a particular ethnolinguistic group is present or represented within a specified place, context, or population.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decaa1e9ec81908d7c26c1c4e43014 |
completed | April 14, 2026, 11:15 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.