Triple
T9342735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nora Rowley |
E224801
|
entity |
| Predicate | rejects |
P438
|
FINISHED |
| Object | Mr Glascock |
E792829
|
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: Mr Glascock | Statement: [Nora Rowley, rejects, Mr Glascock]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr Glascock Context triple: [Nora Rowley, rejects, Mr Glascock]
-
A.
Mr Glascock
chosen
Mr Glascock is a fictional gentleman suitor in Anthony Trollope’s novel "He Knew He Was Right," known for courting Nora Rowley.
-
B.
Mr. Lewisham
Mr. Lewisham is the ambitious young schoolteacher protagonist of H. G. Wells's novel "Love and Mr. Lewisham," whose ideals and aspirations are tested by love and social constraints.
-
C.
Harold Groves
Harold Groves was an American economist and politician known for his influential work on tax policy and public finance.
-
D.
Mr. Woodcock
Mr. Woodcock is a 2007 American comedy film about a man who discovers that his overbearing former gym teacher is engaged to his mother.
-
E.
Gassy Jack Deighton
Gassy Jack Deighton was a 19th-century British-born bar owner and riverboat captain whose saloon helped spur the founding of Vancouver’s historic Gastown district.
- 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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4bb11cd08190b159a6066dd0ebf1 |
completed | April 1, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0f3c197208190bde7850de266fdf0 |
completed | April 4, 2026, 11:19 a.m. |
Created at: March 30, 2026, 7:40 p.m.