Triple
T40182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clementine Churchill |
E794
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | London, England |
E1817
|
NE FINISHED |
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: London, England | Statement: [Clementine Churchill, placeOfDeath, London, England]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: London, England Context triple: [Clementine Churchill, placeOfDeath, London, England]
-
A.
London, England
chosen
London, England is the capital and largest city of the United Kingdom, renowned as a global center for finance, culture, and politics.
-
B.
City of London
The City of London is the historic and financial core of Greater London, renowned as one of the world’s leading global finance and business centers.
-
C.
Middlesex, England
Middlesex, England is a historic county in southeast England that once encompassed much of what is now Greater London.
-
D.
Lexington, England
Lexington, England is a historic English locality whose name was later adopted by the American town of Lexington, Massachusetts.
-
E.
Cambridge, England
Cambridge, England is a historic university city on the River Cam renowned for the University of Cambridge and its longstanding contributions to education, science, and culture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24adf3640819095576e072fb5d9a8 |
completed | Feb. 28, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3161762088190924f3d827a5d3cc8 |
completed | Feb. 28, 2026, 4:21 p.m. |
Created at: Feb. 28, 2026, 1:46 a.m.