Triple
T3857982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bilen |
E90064
|
entity |
| Predicate | neighboringLanguages |
P16383
|
FINISHED |
| Object | Saho |
E92654
|
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: Saho | Statement: [Bilen, neighboringLanguages, Saho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saho Context triple: [Bilen, neighboringLanguages, Saho]
-
A.
Saho
chosen
Saho is a Cushitic language spoken primarily by the Saho people in Eritrea and neighboring regions of the Horn of Africa.
-
B.
Marichi
Marichi is a revered Vedic sage (one of the Saptarishi) regarded as a mind-born son of Brahma and an important progenitor in Hindu cosmology.
-
C.
Munchi
Munchi is an alternative name for the Tiv language, a Southern Bantoid language spoken primarily in central Nigeria.
-
D.
Tokusuke
Tokusuke is the given name of Nakae Chōmin, a prominent Japanese political theorist, journalist, and early advocate of liberal democracy in the Meiji era.
-
E.
Zabivaka
Zabivaka is the wolf character that served as the official mascot for major international football tournaments hosted by Russia, including the 2018 FIFA World Cup.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec1e68f88190941c39221486f6ae |
completed | March 9, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b504228220819082e11b316ba79b08 |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:19 p.m.