Triple
T22793665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stormberg |
E564181
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Steynsburg
Steynsburg is a small rural town in the Eastern Cape province of South Africa, historically associated with farming and regional trade.
|
E1555936
|
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: Steynsburg | Statement: [Stormberg, containsTown, Steynsburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steynsburg Context triple: [Stormberg, containsTown, Steynsburg]
-
A.
Steffisburg
Steffisburg is a municipality in the canton of Bern in Switzerland, located near the city of Thun in the Bernese Oberland region.
-
B.
Bergville
Bergville is a small town in KwaZulu-Natal, South Africa, serving as a gateway to the northern Drakensberg mountain region.
-
C.
Arensburg
Arensburg is the former German name for Kuressaare, a historic town and seaside resort on Saaremaa Island in Estonia.
-
D.
Hofstadt
Hofstadt is the maiden surname of Betty Draper, a central character on the television series "Mad Men."
-
E.
Moorreesburg
Moorreesburg is a small agricultural town in South Africa’s Western Cape known for its wheat farming and role as an administrative center in the region.
- 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: Steynsburg Triple: [Stormberg, containsTown, Steynsburg]
Generated description
Steynsburg is a small rural town in the Eastern Cape province of South Africa, historically associated with farming and regional trade.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Steynsburg Target entity description: Steynsburg is a small rural town in the Eastern Cape province of South Africa, historically associated with farming and regional trade.
-
A.
Steffisburg
Steffisburg is a municipality in the canton of Bern in Switzerland, located near the city of Thun in the Bernese Oberland region.
-
B.
Bergville
Bergville is a small town in KwaZulu-Natal, South Africa, serving as a gateway to the northern Drakensberg mountain region.
-
C.
Arensburg
Arensburg is the former German name for Kuressaare, a historic town and seaside resort on Saaremaa Island in Estonia.
-
D.
Hofstadt
Hofstadt is the maiden surname of Betty Draper, a central character on the television series "Mad Men."
-
E.
Moorreesburg
Moorreesburg is a small agricultural town in South Africa’s Western Cape known for its wheat farming and role as an administrative center in the region.
- 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_69e2458185f88190b0045227ee420411 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cd751f081909c7907c96c9906ea |
completed | April 29, 2026, 3:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b9e93d1588190a221906ce5a4d834 |
completed | May 18, 2026, 11:19 p.m. |
| NEDg | Description generation | batch_6a0ba2ab22848190a11ebb3514d416f4 |
completed | May 18, 2026, 11:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ba33d87248190ad15c4c72c671fec |
completed | May 18, 2026, 11:39 p.m. |
Created at: April 17, 2026, 3:30 p.m.