Triple
T748575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Baker |
E15395
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Susan Garrett
Susan Garrett is known primarily as the wife of former U.S. Secretary of State and Treasury James A. Baker III.
|
E252144
|
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: Susan Garrett | Statement: [James Baker, spouse, Susan Garrett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susan Garrett Context triple: [James Baker, spouse, Susan Garrett]
-
A.
Kate Garvey
Kate Garvey is a British public relations executive and former political aide, known for her work with Tony Blair and her marriage to Wikipedia co-founder Jimmy Wales.
-
B.
Lisa Rogers
Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
-
C.
Laura Jarrett
Laura Jarrett is an American attorney and journalist known for her work as a legal correspondent on major U.S. news networks.
-
D.
Jennifer Grant
Jennifer Grant is an American actress and the daughter of classic Hollywood film star Cary Grant.
-
E.
Melissa Mathison
Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
- 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: Susan Garrett Triple: [James Baker, spouse, Susan Garrett]
Generated description
Susan Garrett is known primarily as the wife of former U.S. Secretary of State and Treasury James A. Baker III.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Susan Garrett Target entity description: Susan Garrett is known primarily as the wife of former U.S. Secretary of State and Treasury James A. Baker III.
-
A.
Kate Garvey
Kate Garvey is a British public relations executive and former political aide, known for her work with Tony Blair and her marriage to Wikipedia co-founder Jimmy Wales.
-
B.
Lisa Rogers
Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
-
C.
Laura Jarrett
Laura Jarrett is an American attorney and journalist known for her work as a legal correspondent on major U.S. news networks.
-
D.
Jennifer Grant
Jennifer Grant is an American actress and the daughter of classic Hollywood film star Cary Grant.
-
E.
Melissa Mathison
Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
- 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62f31888190b80cb0a7220f8d80 |
completed | March 1, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7eb1ce708190b881655b0813a687 |
completed | March 9, 2026, 8:02 a.m. |
| NEDg | Description generation | batch_69ae7f701cc48190a5ca5320ac15117d |
completed | March 9, 2026, 8:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae7ff1fb748190961febf3790f03cf |
completed | March 9, 2026, 8:08 a.m. |
Created at: March 1, 2026, 7:37 p.m.