Triple
T4592292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arnhemmer |
E103520
|
entity |
| Predicate | belongsToDemonymSystemOf |
P49650
|
FINISHED |
| Object | Dutch cities |
—
|
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: Dutch cities | Statement: [Arnhemmer, belongsToDemonymSystemOf, Dutch cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToDemonymSystemOf Context triple: [Arnhemmer, belongsToDemonymSystemOf, Dutch cities]
-
A.
hasDemonym
Indicates that one entity is the term (demonym) used to refer to the inhabitants or natives of another entity (typically a place).
-
B.
relatedDemonym
chosen
Indicates that one entity is the demonym (name for residents or natives) associated with the other entity.
-
C.
hasEthnonymCountry
Indicates that an ethnonym (a name for an ethnic group or people) is associated with or pertains to a specific country.
-
D.
hasExonym
Indicates that one entity is known by an alternative name or designation in another language or cultural context.
-
E.
administrativeTerritorialEntityOf
Indicates that one entity serves as the administrative territorial unit or jurisdiction to which another entity belongs or is governed by.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd592520ec8190b1bd4cb4d9b94c94 |
completed | March 20, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69bd522acbcc8190bf24d9517793a2c1 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:11 p.m.