Triple
T864407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fleming |
E18669
|
entity |
| Predicate | derivedFromEthnonym |
P4709
|
FINISHED |
| Object | Fleming (person from Flanders) |
—
|
LITERAL 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 (person from Flanders) | Statement: [Fleming, derivedFromEthnonym, Fleming (person from Flanders)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: derivedFromEthnonym Context triple: [Fleming, derivedFromEthnonym, Fleming (person from Flanders)]
-
A.
ethnonym
chosen
Indicates that one entity is the name of an ethnic group used to refer to the people associated with another entity.
-
B.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
-
C.
ethnicOrigin
Indicates the relationship where an entity is associated with a particular ethnic group or ancestry.
-
D.
etymology
Indicates the historical origin and development of a word or term, including its source language and form.
-
E.
hasNameOrigin
Indicates that the origin or source of an entity’s name is specified by the related entity.
- F. None of above.
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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac6956488190a5644cdd5b55684f |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa86065881909d477e26fdd84d45 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.