Triple
T457216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germans |
E7258
|
entity |
| Predicate | relatedEthnicGroup |
P1969
|
FINISHED |
| Object | Flemings |
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: Flemings | Statement: [Germans, relatedEthnicGroup, Flemings]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flemings Context triple: [Germans, relatedEthnicGroup, Flemings]
-
A.
Foege
Foege is the surname of William H. Foege, an American epidemiologist renowned for his pivotal role in the global eradication of smallpox.
-
B.
Fleming
chosen
Fleming is a surname most famously associated with Ian Fleming, the British author who created the James Bond spy novels.
-
C.
Southery
Southery is a village and civil parish in Norfolk, England, situated in the Fens near the River Great Ouse.
-
D.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
-
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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa1616481909399f92551a0c9e3 |
completed | Feb. 28, 2026, 1:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a44cbecca48190ab10a14ed0037339 |
completed | March 1, 2026, 2:27 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.