Triple
T346700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pashto language |
E6957
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Wanetsi
Wanetsi is a distinct and archaic variety of Pashto spoken by a small community in parts of Afghanistan and Pakistan.
|
E46312
|
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: Wanetsi | Statement: [Pashto language, hasDialect, Wanetsi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wanetsi Context triple: [Pashto language, hasDialect, Wanetsi]
-
A.
Kibondo
Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
-
B.
Terevaka
Terevaka is a large extinct volcanic peak that forms the highest and youngest of the three main volcanoes making up Easter Island.
-
C.
Kasulu
Kasulu is a town in western Tanzania that serves as one of the main urban and commercial centers of the Kigoma Region.
-
D.
Keteleeria
Keteleeria is a small genus of evergreen coniferous trees native to East and Southeast Asia, known for their tall stature and resemblance to firs and spruces.
-
E.
Amenia
Amenia is a small rural town in eastern Dutchess County, New York, known for its scenic Hudson Valley landscapes and historic character.
- 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: Wanetsi Triple: [Pashto language, hasDialect, Wanetsi]
Generated description
Wanetsi is a distinct and archaic variety of Pashto spoken by a small community in parts of Afghanistan and Pakistan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wanetsi Target entity description: Wanetsi is a distinct and archaic variety of Pashto spoken by a small community in parts of Afghanistan and Pakistan.
-
A.
Kibondo
Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
-
B.
Terevaka
Terevaka is a large extinct volcanic peak that forms the highest and youngest of the three main volcanoes making up Easter Island.
-
C.
Kasulu
Kasulu is a town in western Tanzania that serves as one of the main urban and commercial centers of the Kigoma Region.
-
D.
Keteleeria
Keteleeria is a small genus of evergreen coniferous trees native to East and Southeast Asia, known for their tall stature and resemblance to firs and spruces.
-
E.
Amenia
Amenia is a small rural town in eastern Dutchess County, New York, known for its scenic Hudson Valley landscapes and historic character.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1a37c08190b1380f6bf8513a37 |
completed | Feb. 28, 2026, 1:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3e85ff5248190848e7c390d550c59 |
completed | March 1, 2026, 7:18 a.m. |
| NEDg | Description generation | batch_69a3e94164408190b8b805f5752efa38 |
completed | March 1, 2026, 7:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3ea90ddfc819087479810f42ce591 |
completed | March 1, 2026, 7:28 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.