Triple
T1237125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Wesley |
E26573
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wesley |
E41148
|
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: Wesley | Statement: [John Wesley, familyName, Wesley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wesley Context triple: [John Wesley, familyName, Wesley]
-
A.
Wesley
chosen
Wesley is a masculine given name of English origin, traditionally used in English-speaking countries.
-
B.
John Wesley
John Wesley was an 18th-century Anglican cleric and theologian who founded Methodism and became a central figure in the rise of modern evangelical Christianity.
-
C.
Samuel Church
Samuel Church is a notable individual who bears the English surname "Church," recognized for his significance among people with that family name.
-
D.
Elisha Whittlesey
Elisha Whittlesey was a 19th-century American lawyer and politician from Ohio who served in the U.S. House of Representatives and later held key federal financial oversight roles.
-
E.
John Luther
John Luther is a brilliant but tormented London detective from the British crime drama series "Luther," known for his obsessive pursuit of justice and morally ambiguous methods.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf3f07c08190a402e8341c1f38cc |
completed | March 1, 2026, 10:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8f75778881908c9c3ea6f8b3392a |
completed | March 7, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:47 p.m.