Triple
T16751626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beti–Pahuin languages |
E407094
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object | Beti |
E1198359
|
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: Beti | Statement: [Beti–Pahuin languages, hasLanguage, Beti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beti Context triple: [Beti–Pahuin languages, hasLanguage, Beti]
-
A.
Beti
chosen
The Beti are a Central African ethnic group primarily inhabiting central Cameroon, known for their Bantu language, rich oral traditions, and influential cultural and political role in the region.
-
B.
Nubeena
Nubeena is a small coastal town on Tasmania’s Tasman Peninsula known as a local service and tourism hub for the surrounding rural and scenic areas.
-
C.
बरामती
बरामती महाराष्ट्रातील पुणे जिल्ह्यातील एक ऐतिहासिक व कृषीप्रधान शहर आहे, जे औद्योगिक विकास आणि राजकीय महत्त्वासाठी ओळखले जाते.
-
D.
Tanuja
Tanuja is a veteran Indian film actress known for her work in Hindi and Bengali cinema and as a prominent member of the Mukherjee-Samarth film family.
-
E.
Ketaki
Ketaki is a central female character in Rabindranath Tagore’s novel "Shesher Kobita," known for her modern outlook and complex romantic relationship with the protagonist, Amit.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa271de48190b4a535408aeef734 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52402848190b029cb0be31b4c74 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.