Triple
T9479597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Zealand national swimming team |
E228599
|
entity |
| Predicate | hasNotableSwimmer |
P9730
|
FINISHED |
| Object |
Lauren Boyle
Lauren Boyle is a New Zealand freestyle swimmer and multiple World Championship medallist known for her success in middle- and long-distance events.
|
E811170
|
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 Boyle | Statement: [New Zealand national swimming team, hasNotableSwimmer, Lauren Boyle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauren Boyle Context triple: [New Zealand national swimming team, hasNotableSwimmer, Lauren Boyle]
-
A.
Lauren Booth
Lauren Booth is a British journalist, broadcaster, and activist known for her work in media and her high-profile conversion to Islam.
-
B.
Lauren Baker
Lauren Baker is an American nonprofit leader and public figure who served as First Lady of Massachusetts during Charlie Baker’s governorship.
-
C.
Lauren Lloyd
Lauren Lloyd is a film producer best known for her work on the 1990 coming-of-age drama "Mermaids."
-
D.
Lauren Jones
Lauren Jones is an American model, actress, and television personality known for her appearances in film, TV, and professional wrestling.
-
E.
Lauren Barber
Lauren Barber is best known as the wife of English musician and actor Gary Kemp.
- 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 Boyle Triple: [New Zealand national swimming team, hasNotableSwimmer, Lauren Boyle]
Generated description
Lauren Boyle is a New Zealand freestyle swimmer and multiple World Championship medallist known for her success in middle- and long-distance events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lauren Boyle Target entity description: Lauren Boyle is a New Zealand freestyle swimmer and multiple World Championship medallist known for her success in middle- and long-distance events.
-
A.
Lauren Booth
Lauren Booth is a British journalist, broadcaster, and activist known for her work in media and her high-profile conversion to Islam.
-
B.
Lauren Baker
Lauren Baker is an American nonprofit leader and public figure who served as First Lady of Massachusetts during Charlie Baker’s governorship.
-
C.
Lauren Lloyd
Lauren Lloyd is a film producer best known for her work on the 1990 coming-of-age drama "Mermaids."
-
D.
Lauren Jones
Lauren Jones is an American model, actress, and television personality known for her appearances in film, TV, and professional wrestling.
-
E.
Lauren Barber
Lauren Barber is best known as the wife of English musician and actor Gary Kemp.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd8016813881908dafc026779c89c4 |
completed | April 1, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1820ba67881909955c4198c7289b1 |
completed | April 4, 2026, 9:26 p.m. |
| NEDg | Description generation | batch_69d182b613348190917338a8f0b896bb |
completed | April 4, 2026, 9:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1835c916081908e3e1bb1e5499424 |
completed | April 4, 2026, 9:32 p.m. |
Created at: March 30, 2026, 7:54 p.m.