Triple
T8396074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramsey Clark |
E198053
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Georgia Welch
Georgia Welch is best known as the wife of former U.S. Attorney General and prominent civil rights advocate Ramsey Clark.
|
E825665
|
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: Georgia Welch | Statement: [Ramsey Clark, spouse, Georgia Welch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georgia Welch Context triple: [Ramsey Clark, spouse, Georgia Welch]
-
A.
Mary Wheeler
Mary Wheeler is a sibling of the renowned American theoretical physicist John Archibald Wheeler.
-
B.
Mary Woodvine
Mary Woodvine is a British actress known for her work in television dramas and films, often appearing in character-driven and crime-related series.
-
C.
Sarah Winston
Sarah Winston was a colonial American woman best known as the mother of Founding Father and second U.S. President John Adams.
-
D.
Ruby Thewes
Ruby Thewes is a tough, resourceful mountain woman in Charles Frazier’s novel (and its film adaptation) "Cold Mountain," known for helping Ada Monroe survive and adapt to rural farm life during the Civil War.
-
E.
Moss Evans
Moss Evans was a prominent British trade union leader who headed one of the UK’s largest and most influential unions during the late 20th century.
- 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: Georgia Welch Triple: [Ramsey Clark, spouse, Georgia Welch]
Generated description
Georgia Welch is best known as the wife of former U.S. Attorney General and prominent civil rights advocate Ramsey Clark.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Georgia Welch Target entity description: Georgia Welch is best known as the wife of former U.S. Attorney General and prominent civil rights advocate Ramsey Clark.
-
A.
Mary Wheeler
Mary Wheeler is a sibling of the renowned American theoretical physicist John Archibald Wheeler.
-
B.
Mary Woodvine
Mary Woodvine is a British actress known for her work in television dramas and films, often appearing in character-driven and crime-related series.
-
C.
Sarah Winston
Sarah Winston was a colonial American woman best known as the mother of Founding Father and second U.S. President John Adams.
-
D.
Ruby Thewes
Ruby Thewes is a tough, resourceful mountain woman in Charles Frazier’s novel (and its film adaptation) "Cold Mountain," known for helping Ada Monroe survive and adapt to rural farm life during the Civil War.
-
E.
Moss Evans
Moss Evans was a prominent British trade union leader who headed one of the UK’s largest and most influential unions during the late 20th century.
- 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb81874d6c8190bbc0ac832d8a339d |
completed | March 31, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e3d6191c8190adb41feec1bfa76e |
completed | April 5, 2026, 4:23 a.m. |
| NEDg | Description generation | batch_69d1e5204f748190b1f56ee5469828a2 |
completed | April 5, 2026, 4:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1e598243481909278cb3c911ce3db |
completed | April 5, 2026, 4:31 a.m. |
Created at: March 30, 2026, 6:04 p.m.