Triple
T15407141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alago |
E368489
|
entity |
| Predicate | language |
P15
|
FINISHED |
| Object | Alago language |
E1070888
|
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: Alago language | Statement: [Alago, language, Alago language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alago language Context triple: [Alago, language, Alago language]
-
A.
Alago language
chosen
The Alago language is a Niger-Congo language spoken by the Alago people of central Nigeria.
-
B.
Alagwa language
The Alagwa language is a South Cushitic language spoken by the Alagwa people of north-central Tanzania.
-
C.
Warao language
The Warao language is an indigenous language isolate spoken by the Warao people of northeastern Venezuela and nearby regions, particularly in the Orinoco Delta.
-
D.
Apurinã language
The Apurinã language is an indigenous Arawakan language spoken by the Apurinã people of the Brazilian Amazon, known for its complex verbal morphology and endangered status.
-
E.
Galela language
The Galela language is an Austronesian language spoken by the Galela people in northern Halmahera, Indonesia.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea36c6881909eaea48e9608897a |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff135a26f08190ad3fc1d5a263a24e |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:20 a.m.