Triple
T21041403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beggar Woman |
E518333
|
entity |
| Predicate | victimOf |
P870
|
FINISHED |
| Object | Judge Turpin |
—
|
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: Judge Turpin | Statement: [Beggar Woman, victimOf, Judge Turpin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Judge Turpin Context triple: [Beggar Woman, victimOf, Judge Turpin]
-
A.
Judge Turpin
chosen
Judge Turpin is the corrupt, tyrannical magistrate and primary antagonist in the musical "Sweeney Todd: The Demon Barber of Fleet Street."
-
B.
Will Turpin
Will Turpin is an American musician best known as the longtime bassist for the rock band Collective Soul.
-
C.
Baron Weatherill
Baron Weatherill was a British Conservative politician who served as Speaker of the House of Commons from 1983 to 1992.
-
D.
Judge George Jeffreys
Judge George Jeffreys was a 17th-century English jurist infamous for his brutal conduct during the "Bloody Assizes" following the Monmouth Rebellion.
-
E.
James Mortmain
James Mortmain is the eccentric, reclusive father and struggling writer in the romantic drama film "I Capture the Castle."
- 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_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fcefe4688190ad1bed1ef2d7a3e5 |
completed | April 21, 2026, 4:28 a.m. |
Created at: April 16, 2026, 2:15 p.m.