Triple
T10043134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cushitic |
E205344
|
entity |
| Predicate | includesLanguage |
P2177
|
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: [Cushitic, includesLanguage, Saho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saho Context triple: [Cushitic, includesLanguage, 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.
Saaho
Saaho is a 2019 Indian action thriller film known for its high-budget production, elaborate action sequences, and starring Prabhas in the lead role.
-
C.
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.
-
D.
Katano
Katano is a city in Osaka Prefecture, Japan, known for its residential suburbs and proximity to the Osaka metropolitan area.
-
E.
Wacho
Wacho was a 6th-century king of the Lombards known for consolidating royal power and shaping the early history of the Lombard kingdom in Central Europe.
- 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcf60a2208190846e57b5f5649307 |
completed | April 2, 2026, 2:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d28278235c8190a5e833a9586bd3f5 |
completed | April 5, 2026, 3:40 p.m. |
Created at: March 30, 2026, 8:55 p.m.