Triple
T3515534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of London School |
E74297
|
entity |
| Predicate | hasNotableAlumnus |
P51
|
FINISHED |
| Object | Daniel Radcliffe |
E95151
|
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: Daniel Radcliffe | Statement: [City of London School, hasNotableAlumnus, Daniel Radcliffe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Radcliffe Context triple: [City of London School, hasNotableAlumnus, Daniel Radcliffe]
-
A.
Daniel Radcliffe
chosen
Daniel Radcliffe is an English actor best known for playing the title role in the Harry Potter film series.
-
B.
Rupert Grint
Rupert Grint is an English actor best known for playing Ron Weasley in the Harry Potter film series.
-
C.
Liam Aiken
Liam Aiken is an American actor known for his roles as a child and teen in films such as "A Series of Unfortunate Events," "Good Boy!" and "Stepmom."
-
D.
Rupert Friend
Rupert Friend is an English actor known for roles in films like "Pride & Prejudice" and the TV series "Homeland."
-
E.
Fionn Whitehead
Fionn Whitehead is a British actor best known for his breakout leading role in Christopher Nolan’s World War II film "Dunkirk."
- 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc30362c81908ca7497a6a935cc6 |
completed | March 8, 2026, 6:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e7a5ab08190971c9dfd6550eb2d |
completed | March 13, 2026, 3:03 a.m. |
Created at: March 8, 2026, 3:19 p.m.