Triple
T873007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Fleming |
E18855
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fleming |
E18669
|
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: Fleming | Statement: [Peter Fleming, familyName, Fleming]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fleming Context triple: [Peter Fleming, familyName, Fleming]
-
A.
Fleming
chosen
Fleming is a surname most famously associated with Ian Fleming, the British author who created the James Bond spy novels.
-
B.
Flemming
Flemming is a surname and given name of Germanic origin, used by various notable individuals across fields such as politics, arts, and science.
-
C.
Flemings
Flemings are a Dutch-speaking ethnic group from the northern region of Belgium, primarily associated with Flanders and known for their distinct cultural and linguistic identity.
-
D.
Ehrlich
Ehrlich is a German-origin surname borne by numerous notable individuals across fields such as science, medicine, and the arts.
-
E.
Faulks
Faulks is the surname of British novelist and journalist Sebastian Faulks, best known for his historical and literary fiction.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac97d0f88190b67fcb7fc058e4b9 |
completed | March 1, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b84fb2d0819084c256023bc23dc5 |
completed | March 4, 2026, 4:42 a.m. |
Created at: March 1, 2026, 7:39 p.m.