Triple
T1604692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ga people |
E34474
|
entity |
| Predicate | language |
P15
|
FINISHED |
| Object | Ga language |
E155048
|
NE 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: Ga language | Statement: [Ga people, language, Ga language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ga language Context triple: [Ga people, language, Ga language]
-
A.
Ga language
chosen
The Ga language is a Niger-Congo language spoken primarily by the Ga people in and around Accra, the capital of Ghana.
-
B.
Gane language
The Gane language is an Austronesian language spoken by the Gane people in the southern part of Halmahera in eastern Indonesia.
-
C.
Gbaya languages
The Gbaya languages are a group of closely related Niger-Congo languages spoken primarily in the Central African Republic and neighboring regions by the Gbaya people.
-
D.
Gedaged language
Gedaged is an Austronesian language of the Western Oceanic branch spoken in coastal areas of Papua New Guinea.
-
E.
Ha language
Ha language is a Bantu language spoken primarily by the Ha people in western Tanzania, particularly around the shores of Lake Tanganyika.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9096a165c8190aec1d2ae6bd10e18 |
completed | March 5, 2026, 4:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad51bcdebc81909520786c560598b6 |
completed | March 8, 2026, 10:38 a.m. |
Created at: March 4, 2026, 7:28 p.m.