Triple
T3131825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Baker |
E65431
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Lauren Baker
Lauren Baker is an American nonprofit leader and public figure who served as First Lady of Massachusetts during Charlie Baker’s governorship.
|
E370706
|
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: Lauren Baker | Statement: [Charlie Baker, spouse, Lauren Baker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauren Baker Context triple: [Charlie Baker, spouse, Lauren Baker]
-
A.
Lauren Barber
Lauren Barber is best known as the wife of English musician and actor Gary Kemp.
-
B.
Lauren Beck
Lauren Beck is a film producer best known for her work on the critically acclaimed drama "Manchester by the Sea."
-
C.
Courtney Lemmon
Courtney Lemmon is the daughter of acclaimed American actor Jack Lemmon and is known for her work as a jazz and blues singer.
-
D.
Natalie Desselle
Natalie Desselle was an American actress best known for her comedic roles in film and television, including her memorable performance in the 1997 adaptation of "Cinderella."
-
E.
Jenna McMahon
Jenna McMahon was an American television writer and producer best known for co-creating popular sitcoms such as "The Facts of Life" and "Mama's Family."
- 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: Lauren Baker Triple: [Charlie Baker, spouse, Lauren Baker]
Generated description
Lauren Baker is an American nonprofit leader and public figure who served as First Lady of Massachusetts during Charlie Baker’s governorship.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lauren Baker Target entity description: Lauren Baker is an American nonprofit leader and public figure who served as First Lady of Massachusetts during Charlie Baker’s governorship.
-
A.
Lauren Barber
Lauren Barber is best known as the wife of English musician and actor Gary Kemp.
-
B.
Lauren Beck
Lauren Beck is a film producer best known for her work on the critically acclaimed drama "Manchester by the Sea."
-
C.
Courtney Lemmon
Courtney Lemmon is the daughter of acclaimed American actor Jack Lemmon and is known for her work as a jazz and blues singer.
-
D.
Natalie Desselle
Natalie Desselle was an American actress best known for her comedic roles in film and television, including her memorable performance in the 1997 adaptation of "Cinderella."
-
E.
Jenna McMahon
Jenna McMahon was an American television writer and producer best known for co-creating popular sitcoms such as "The Facts of Life" and "Mama's Family."
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada55f77b881908866fc43bdb18185 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b402b6f23081909aea1345a2938113 |
completed | March 13, 2026, 12:27 p.m. |
| NEDg | Description generation | batch_69b406bfa0588190a20d862a6f788c90 |
completed | March 13, 2026, 12:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4086ab034819086c5fa7d4b172d75 |
completed | March 13, 2026, 12:51 p.m. |
Created at: March 8, 2026, 3:04 p.m.