Triple
T5258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Harvard |
E103
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Southwark |
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: Southwark | Statement: [John Harvard, birthPlace, Southwark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Southwark Context triple: [John Harvard, birthPlace, Southwark]
-
A.
Surrey
Surrey is a county in southeast England known for its historic towns, affluent suburbs, and proximity to London.
-
B.
Manchester Victoria
Manchester Victoria is a major railway station in Manchester city centre, serving as a key hub for regional and local train services across northern England.
-
C.
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.
-
D.
Gloucester
Gloucester is a historic coastal city in northeastern Massachusetts known for its long-standing fishing industry and maritime heritage.
-
E.
London Breed
London Breed is an American politician serving as the mayor of San Francisco and the first Black woman to hold that office.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a2399d5cf88190998f9b95c817a60f |
completed | Feb. 28, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a25528aa18819088213f16547924ca |
completed | Feb. 28, 2026, 2:38 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.