Triple
T17266088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Monro |
E419130
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Monro |
E711142
|
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: Monro | Statement: [Charles Monro, familyName, Monro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monro Context triple: [Charles Monro, familyName, Monro]
-
A.
Monro
chosen
Monro is a variant spelling of the Scottish surname Munro, historically associated with a Highland clan from Easter Ross.
-
B.
Munroe
Munroe is a surname of Scottish origin borne by various notable individuals across fields such as politics, sports, and the arts.
-
C.
Monrow
Monrow is an alternative spelling of the name Monroe, which is commonly used as both a surname and given name and is associated with various notable people and places.
-
D.
Moncure
Moncure is a masculine given name most notably borne by the American abolitionist and writer Moncure Daniel Conway.
-
E.
Peniston
Peniston is a masculine given name of English origin, historically borne by several members of the British aristocracy.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f44ec7c81909a925fc8692b0a6c |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01794641648190a5db87ecb359c17a |
completed | May 11, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:40 a.m.