Triple
T10501132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Alfege |
E247674
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Alfege |
E867299
|
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: Alfege | Statement: [Saint Alfege, givenName, Alfege]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alfege Context triple: [Saint Alfege, givenName, Alfege]
-
A.
Alfege
chosen
Alfege is an Anglo-Saxon saint and Archbishop of Canterbury, venerated for his martyrdom after refusing to allow a ransom to be paid for his release from Viking captors.
-
B.
Allfrey
Allfrey is an English surname borne by various notable individuals, including military figures and writers.
-
C.
Foulke
Foulke is a surname most notably associated with former Major League Baseball relief pitcher Keith Foulke.
-
D.
Galfard
Galfard is the surname of Christophe Galfard, a French theoretical physicist and science communicator known for his popular science books.
-
E.
Fages
Fages is a Spanish surname most notably associated with Pedro Fages, an 18th-century Spanish soldier and colonial administrator in California.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5099b797c8190a94803fa94eb6981 |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90ddbbb3c8190873e8e3c27039b16 |
completed | April 10, 2026, 2:48 p.m. |
Created at: April 6, 2026, 12:25 p.m.