Triple
T16334181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friedrich Welwitsch |
E396633
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Welwitsch
Welwitsch is a surname most notably associated with Austrian botanist Friedrich Welwitsch, after whom the unique desert plant Welwitschia is named.
|
E1207183
|
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: Welwitsch | Statement: [Friedrich Welwitsch, familyName, Welwitsch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Welwitsch Context triple: [Friedrich Welwitsch, familyName, Welwitsch]
-
A.
Tchagra
Tchagra is a genus of African bushshrikes, medium-sized passerine birds known for their strong hooked bills and distinctive head patterns.
-
B.
Bulebel
Bulebel is an industrial and residential area forming part of the town of Żejtun in Malta.
-
C.
Chivi
Chivi is a rural district and settlement in southern Zimbabwe known for its communal farming communities and semi-arid landscape within Masvingo Province.
-
D.
Chirisa
Chirisa is a surname most notably associated with Zimbabwean actor Tongayi Chirisa, known for his roles in film and television.
-
E.
Garango
Garango is a town in Burkina Faso known for its cultural and municipal ties with the German town of Ladenburg.
- 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: Welwitsch Triple: [Friedrich Welwitsch, familyName, Welwitsch]
Generated description
Welwitsch is a surname most notably associated with Austrian botanist Friedrich Welwitsch, after whom the unique desert plant Welwitschia is named.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Welwitsch Target entity description: Welwitsch is a surname most notably associated with Austrian botanist Friedrich Welwitsch, after whom the unique desert plant Welwitschia is named.
-
A.
Tchagra
Tchagra is a genus of African bushshrikes, medium-sized passerine birds known for their strong hooked bills and distinctive head patterns.
-
B.
Bulebel
Bulebel is an industrial and residential area forming part of the town of Żejtun in Malta.
-
C.
Chivi
Chivi is a rural district and settlement in southern Zimbabwe known for its communal farming communities and semi-arid landscape within Masvingo Province.
-
D.
Chirisa
Chirisa is a surname most notably associated with Zimbabwean actor Tongayi Chirisa, known for his roles in film and television.
-
E.
Garango
Garango is a town in Burkina Faso known for its cultural and municipal ties with the German town of Ladenburg.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4e1da1081909bec6e77e6109dce |
completed | April 17, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0026173dc081909e00f6647d1f68b3 |
completed | May 10, 2026, 6:30 a.m. |
| NEDg | Description generation | batch_6a00286f9e4c8190b01e75d2bfe3083a |
completed | May 10, 2026, 6:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0028e71de88190b48e33f2116e78dc |
completed | May 10, 2026, 6:42 a.m. |
Created at: April 10, 2026, 5:07 a.m.