Triple
T33214640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gronings |
E850254
|
entity |
| Predicate | hasLocalNameForSiddeburen |
P24351
|
FINISHED |
| Object | Siddebör’n |
—
|
NE NERFINISHED |
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: Siddebör’n | Statement: [Gronings, hasLocalNameForSiddeburen, Siddebör’n]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalNameForSiddeburen Context triple: [Gronings, hasLocalNameForSiddeburen, Siddebör’n]
-
A.
hasLocalNameFor
chosen
Indicates that one entity serves as the local or context-specific name or label used to refer to another entity.
-
B.
hasLocalNameForRiver
Indicates that an entity specifies the locally used name for a particular river.
-
C.
hasNameInMunicipality
Indicates that an entity is known by a particular name within the context or jurisdiction of a specific municipality.
-
D.
hasNameInLocalLanguage
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
-
E.
hasNameInBelgium
Indicates that an entity is known or referred to by a particular name specifically within the context of Belgium.
- 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_69f3495fb92c819083ce65d0ddee7a76 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe6fea4a288190bf8615c5d6bf41b4 |
completed | May 8, 2026, 11:21 p.m. |
| PD | Predicate disambiguation | batch_69fe6f774de08190975a2393b9a1fd22 |
completed | May 8, 2026, 11:19 p.m. |
Created at: May 1, 2026, 1:30 a.m.