Triple
T451054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geoffrey Chaucer |
E7129
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Geoffrey |
E28362
|
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: Geoffrey | Statement: [Geoffrey Chaucer, givenName, Geoffrey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geoffrey Context triple: [Geoffrey Chaucer, givenName, Geoffrey]
-
A.
Geoffrey
chosen
Geoffrey is a masculine given name of English origin, famously borne by pioneering computer scientist and AI researcher Geoffrey Hinton.
-
B.
Guillaume
Guillaume is the French form of the given name William, commonly used in French-speaking countries.
-
C.
Roger de Montgomery
Roger de Montgomery was an 11th-century Norman nobleman and close ally of William the Conqueror who became Earl of Shrewsbury and a major landholder in post-Conquest England.
-
D.
Gaston de Blondeville
Gaston de Blondeville is a historical Gothic romance novel by Ann Radcliffe, set in medieval England and blending chivalric adventure with supernatural elements.
-
E.
Wilfred
Wilfred is a masculine given name of English origin, notably borne by the World War I poet Wilfred Owen.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef835ae881908884dcc3a46af951 |
completed | Feb. 28, 2026, 1:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a44f555b988190b3c060261dc811df |
completed | March 1, 2026, 2:38 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.