Triple
T20699755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antony Booth |
E508747
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Lauren Booth |
—
|
NE NERFINISHED |
How this triple was built (2 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 Booth | Statement: [Antony Booth, child, Lauren Booth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauren Booth Context triple: [Antony Booth, child, Lauren Booth]
-
A.
Lauren Booth
chosen
Lauren Booth is a British journalist, broadcaster, and activist known for her work in media and her high-profile conversion to Islam.
-
B.
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.
-
C.
Lauren Poultney
Lauren Poultney is a senior British police officer who serves as the Chief Constable of South Yorkshire Police.
-
D.
Lauren German
Lauren German is an American actress known for her roles in films like "A Walk to Remember" and TV series such as "Chicago Fire" and "Lucifer."
-
E.
Lauren Baker
Lauren Baker is an American nonprofit leader and public figure who served as First Lady of Massachusetts during Charlie Baker’s governorship.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c2b2a481909e31e9cb8f81ab55 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c18a77308190b7c2517d82a145cd |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 12:12 p.m.