Triple
T15944809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Omotic |
E386656
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object |
Ganza language
Ganza language is a lesser-known Afroasiatic language spoken by communities in southwestern Ethiopia and neighboring regions.
|
E1185211
|
NE FINISHED |
How this triple was built (4 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: Ganza language | Statement: [North Omotic, hasLanguage, Ganza language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ganza language Context triple: [North Omotic, hasLanguage, Ganza language]
-
A.
Gonja language
The Gonja language is a Gur language spoken primarily by the Gonja people in northern 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.
Nganasan language
The Nganasan language is a critically endangered Samoyedic language spoken by the Nganasan people of the Taymyr Peninsula in northern Siberia.
-
D.
Ghanongga language
The Ghanongga language is an Oceanic language spoken by indigenous communities on New Georgia Island in the Solomon Islands.
-
E.
Ganguela language
The Ganguela language is a Bantu language spoken by the Ganguela people of southwestern Africa, particularly in Angola.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ganza language Triple: [North Omotic, hasLanguage, Ganza language]
Generated description
Ganza language is a lesser-known Afroasiatic language spoken by communities in southwestern Ethiopia and neighboring regions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ganza language Target entity description: Ganza language is a lesser-known Afroasiatic language spoken by communities in southwestern Ethiopia and neighboring regions.
-
A.
Gonja language
The Gonja language is a Gur language spoken primarily by the Gonja people in northern 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.
Nganasan language
The Nganasan language is a critically endangered Samoyedic language spoken by the Nganasan people of the Taymyr Peninsula in northern Siberia.
-
D.
Ghanongga language
The Ghanongga language is an Oceanic language spoken by indigenous communities on New Georgia Island in the Solomon Islands.
-
E.
Ganguela language
The Ganguela language is a Bantu language spoken by the Ganguela people of southwestern Africa, particularly in Angola.
- F. None of above. chosen
Provenance (5 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156d016588190ae368197dfa7d43a |
completed | April 16, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5beabbc8190977f14c1b3ccdf29 |
completed | May 9, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69ffb677927c8190bd45e7bae5fcf1ed |
completed | May 9, 2026, 10:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb7468fb88190a56cf1df5bd20f63 |
completed | May 9, 2026, 10:37 p.m. |
Created at: April 10, 2026, 4:53 a.m.