Triple
T6776695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korandje language |
E155575
|
entity |
| Predicate | hasInfluenceFrom |
P9
|
FINISHED |
| Object |
Taznatit
Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
|
E618291
|
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: Taznatit | Statement: [Korandje language, hasInfluenceFrom, Taznatit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taznatit Context triple: [Korandje language, hasInfluenceFrom, Taznatit]
-
A.
La Tzoumaz
La Tzoumaz is a Swiss alpine village and ski resort in the 4 Vallées region, known for its family-friendly slopes and access to extensive interconnected ski terrain.
-
B.
Zezuru
Zezuru is a major dialect of the Shona language spoken primarily in central and northern Zimbabwe.
-
C.
Tayasan
Tayasan is a coastal municipality in the province of Negros Oriental in the Philippines, known for its rural communities and agricultural economy.
-
D.
Tále
Tále is a popular ski resort and recreational area in the Low Tatras mountains of central Slovakia, known for its slopes, golf course, and year-round outdoor activities.
-
E.
Taygi
Taygi is a lesser-known Samoyedic language of the Uralic family traditionally spoken by an indigenous group in northern Siberia.
- 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: Taznatit Triple: [Korandje language, hasInfluenceFrom, Taznatit]
Generated description
Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taznatit Target entity description: Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
-
A.
La Tzoumaz
La Tzoumaz is a Swiss alpine village and ski resort in the 4 Vallées region, known for its family-friendly slopes and access to extensive interconnected ski terrain.
-
B.
Zezuru
Zezuru is a major dialect of the Shona language spoken primarily in central and northern Zimbabwe.
-
C.
Tayasan
Tayasan is a coastal municipality in the province of Negros Oriental in the Philippines, known for its rural communities and agricultural economy.
-
D.
Tále
Tále is a popular ski resort and recreational area in the Low Tatras mountains of central Slovakia, known for its slopes, golf course, and year-round outdoor activities.
-
E.
Taygi
Taygi is a lesser-known Samoyedic language of the Uralic family traditionally spoken by an indigenous group in northern Siberia.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d26725208190b64935cfd08b2aff |
completed | March 27, 2026, 6:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c712cc9ff08190bb7ec0bf4cc4db01 |
completed | March 27, 2026, 11:29 p.m. |
| NEDg | Description generation | batch_69c71396f1f88190b3316e694424a2fe |
completed | March 27, 2026, 11:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c71466728c81909a24174a7938b43a |
completed | March 27, 2026, 11:36 p.m. |
Created at: March 27, 2026, 2:13 p.m.