Triple
T8131921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stapleton Cotton, 1st Viscount Combermere |
E189871
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Cotton
Cotton is a common English surname with historical associations to several notable British families and figures.
|
E713991
|
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: Cotton | Statement: [Stapleton Cotton, 1st Viscount Combermere, familyName, Cotton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cotton Context triple: [Stapleton Cotton, 1st Viscount Combermere, familyName, Cotton]
-
A.
Cotton
Cotton is a soft, natural fiber harvested from the seed pods of cotton plants and widely used in textiles and clothing.
-
B.
Cotten
Cotten is a surname most notably associated with American actor Joseph Cotten, a prominent figure in classic Hollywood cinema.
-
C.
Cotton Market
Cotton Market is a historic commercial area traditionally associated with the trade and sale of cotton and related goods.
-
D.
Cotton Tufts
Cotton Tufts was an 18th-century American physician and patriot from Massachusetts who was active in public affairs during the Revolutionary era.
-
E.
Gossypium
Gossypium is a genus of flowering plants best known for producing cotton, one of the world’s most important natural textile fibers.
- 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: Cotton Triple: [Stapleton Cotton, 1st Viscount Combermere, familyName, Cotton]
Generated description
Cotton is a common English surname with historical associations to several notable British families and figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cotton Target entity description: Cotton is a common English surname with historical associations to several notable British families and figures.
-
A.
Cotton
Cotton is a soft, natural fiber harvested from the seed pods of cotton plants and widely used in textiles and clothing.
-
B.
Cotten
Cotten is a surname most notably associated with American actor Joseph Cotten, a prominent figure in classic Hollywood cinema.
-
C.
Cotton Market
Cotton Market is a historic commercial area traditionally associated with the trade and sale of cotton and related goods.
-
D.
Cotton Tufts
Cotton Tufts was an 18th-century American physician and patriot from Massachusetts who was active in public affairs during the Revolutionary era.
-
E.
Gossypium
Gossypium is a genus of flowering plants best known for producing cotton, one of the world’s most important natural textile fibers.
- 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_69ca82bcb4848190a9a9d036ad768642 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb43b96cd481908c0679050c35d83f |
completed | March 31, 2026, 3:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc9482113881909439c9e43fbc933f |
completed | April 1, 2026, 3:44 a.m. |
| NEDg | Description generation | batch_69cc95c0b19881908521cce5ac0fe197 |
completed | April 1, 2026, 3:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc970698f88190a0869515904e50e3 |
completed | April 1, 2026, 3:54 a.m. |
Created at: March 30, 2026, 5:34 p.m.