Triple
T22793664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stormberg |
E564181
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Molteno
Molteno is a small town in South Africa’s Eastern Cape, historically known for its coal mining and as one of the country’s coldest inhabited places.
|
E1555168
|
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: Molteno | Statement: [Stormberg, containsTown, Molteno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Molteno Context triple: [Stormberg, containsTown, Molteno]
-
A.
Molteno
Molteno is a small town in the Lombardy region of northern Italy, known for its location in the hilly Brianza area and its rail links to nearby cities.
-
B.
Makarora
Makarora is a small rural settlement in New Zealand’s South Island, known as a gateway to outdoor activities and hiking in the Southern Alps region.
-
C.
Morrumbene
Morrumbene is a small town in southern Mozambique known for its rural character within Inhambane Province.
-
D.
Omaruru
Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
-
E.
Mataranka
Mataranka is a small town in Australia's Northern Territory, known for its thermal springs and location near Elsey National Park.
- 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: Molteno Triple: [Stormberg, containsTown, Molteno]
Generated description
Molteno is a small town in South Africa’s Eastern Cape, historically known for its coal mining and as one of the country’s coldest inhabited places.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Molteno Target entity description: Molteno is a small town in South Africa’s Eastern Cape, historically known for its coal mining and as one of the country’s coldest inhabited places.
-
A.
Molteno
Molteno is a small town in the Lombardy region of northern Italy, known for its location in the hilly Brianza area and its rail links to nearby cities.
-
B.
Makarora
Makarora is a small rural settlement in New Zealand’s South Island, known as a gateway to outdoor activities and hiking in the Southern Alps region.
-
C.
Morrumbene
Morrumbene is a small town in southern Mozambique known for its rural character within Inhambane Province.
-
D.
Omaruru
Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
-
E.
Mataranka
Mataranka is a small town in Australia's Northern Territory, known for its thermal springs and location near Elsey National Park.
- 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_6a0b9e9214ec8190a67d9d97c74d5064 |
completed | May 18, 2026, 11:19 p.m. |
| NEDg | Description generation | batch_6a0ba09cd4d48190b00db42dc43db779 |
completed | May 18, 2026, 11:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ba13332588190a73ab3a52825a1fe |
completed | May 18, 2026, 11:30 p.m. |
Created at: April 17, 2026, 3:30 p.m.