Triple
T10758558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Map of Virginia |
E253763
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object |
John Smith
John Smith was an early 17th-century English soldier, explorer, and leader of the Jamestown colony in Virginia, known for his influential writings and maps of the New World.
|
E51677
|
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: John Smith | Statement: [A Map of Virginia, author, John Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Smith Context triple: [A Map of Virginia, author, John Smith]
-
A.
John
John is the husband of Martha Rainsborough.
-
B.
John
John is the given name of John Hays Hammond Jr., an American inventor known for his pioneering work in radio control and naval weaponry.
-
C.
John
John is the given name of Lord Eldon, a prominent British lawyer and politician who served as Lord Chancellor in the early 19th century.
-
D.
John
John is a fictional police detective and main character from the science fiction TV series "Almost Human."
-
E.
John
John is the given name of John Copley, 1st Baron Lyndhurst, a prominent 19th-century British lawyer and politician who served three times as Lord Chancellor.
- 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: John Smith Triple: [A Map of Virginia, author, John Smith]
Generated description
John Smith was an early 17th-century English soldier, explorer, and leader of the Jamestown colony in Virginia, known for his influential writings and maps of the New World.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Smith Target entity description: John Smith was an early 17th-century English soldier, explorer, and leader of the Jamestown colony in Virginia, known for his influential writings and maps of the New World.
-
A.
John Smith
chosen
John Smith was an English soldier, explorer, and leader who played a pivotal role in the establishment and survival of the Jamestown colony in early colonial Virginia.
-
B.
John Smith
John Smith was a delegate from South Carolina who served in the Continental Congress during the American Revolutionary era.
-
C.
John Smith
John Smith is an individual known primarily as the husband of Jane Smith.
-
D.
John Smith
John Smith is a person whose formal given name is John but who is also known by the nickname Johnny Smith.
-
E.
John Smith
John Smith was a 19th-century British officer credited with bringing the Ajanta Caves to modern attention after rediscovering them in 1819.
- F. None of above.
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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d72ea107a48190b6b92bb0df03e517 |
completed | April 9, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb0b5c9d8819088edb21a35d8b0dc |
completed | April 14, 2026, 9:25 p.m. |
| NEDg | Description generation | batch_69deb3ef9d0c8190816dc99ed102e03d |
completed | April 14, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69deb4e471648190a00f3a921b5fb657 |
completed | April 14, 2026, 9:43 p.m. |
Created at: April 8, 2026, 9:15 p.m.