Triple
T3748714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manyame River |
E81272
|
entity |
| Predicate | nearbyTown |
P3883
|
FINISHED |
| Object |
Norton
Norton is a town in Zimbabwe located near the Manyame River, known for its agricultural activities and proximity to the capital, Harare.
|
E384587
|
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: Norton | Statement: [Manyame River, nearbyTown, Norton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norton Context triple: [Manyame River, nearbyTown, Norton]
-
A.
Norton
Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
-
B.
Norton
Norton is a small town in Bristol County, southeastern Massachusetts, known for being home to Wheaton College and several scenic ponds and conservation areas.
-
C.
Norton
Norton is a dark-skinned American grape variety, historically significant in Midwestern and Eastern U.S. winemaking for producing deeply colored, full-bodied red wines with notable disease resistance.
-
D.
Norton
Norton is a residential suburb within the town of Runcorn in Cheshire, England.
-
E.
Symantec
Symantec is a cybersecurity and software company best known for its Norton antivirus products and enterprise security solutions.
- 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: Norton Triple: [Manyame River, nearbyTown, Norton]
Generated description
Norton is a town in Zimbabwe located near the Manyame River, known for its agricultural activities and proximity to the capital, Harare.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Norton Target entity description: Norton is a town in Zimbabwe located near the Manyame River, known for its agricultural activities and proximity to the capital, Harare.
-
A.
Norton
Norton is a residential suburb within the town of Runcorn in Cheshire, England.
-
B.
Norton
Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
-
C.
Norton
Norton is a small town in Bristol County, southeastern Massachusetts, known for being home to Wheaton College and several scenic ponds and conservation areas.
-
D.
Norton
Norton is a dark-skinned American grape variety, historically significant in Midwestern and Eastern U.S. winemaking for producing deeply colored, full-bodied red wines with notable disease resistance.
-
E.
Symantec
Symantec is a cybersecurity and software company best known for its Norton antivirus products and enterprise security solutions.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb6bf95c81909796fbc84995ae05 |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db2f5e9881908c10feafbb569f48 |
completed | March 14, 2026, 3:51 a.m. |
| NEDg | Description generation | batch_69b4df1cfd348190831cc472de055436 |
completed | March 14, 2026, 4:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4df7b2da881908aef158d79c2834c |
completed | March 14, 2026, 4:09 a.m. |
Created at: March 8, 2026, 3:35 p.m.