Triple
T16805088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Groesbeek municipality |
E408459
|
entity |
| Predicate | hadMayor |
P185
|
FINISHED |
| Object | local mayor of Groesbeek |
—
|
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: local mayor of Groesbeek | Statement: [Groesbeek municipality, hadMayor, local mayor of Groesbeek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMayor Context triple: [Groesbeek municipality, hadMayor, local mayor of Groesbeek]
-
A.
hasMayor
chosen
Indicates that one entity serves as the mayor of another entity, typically a city, town, or municipality.
-
B.
hasMayorOffice
Indicates that a particular entity serves as the office or official position held by a mayor of another entity.
-
C.
hasNotableMayor
Indicates that an entity has or had a mayor who is particularly distinguished, prominent, or noteworthy.
-
D.
wonMayoraltyOf
Indicates that one entity won the election to become mayor of a specified place or jurisdiction.
-
E.
hasMayorTerm
Indicates that a specified individual holds or has held the office of mayor for a particular jurisdiction during a defined term.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2cb68508190a05749bad68f7b43 |
completed | April 18, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69e319d0fdb8819088425bd82431640f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.