Triple
T35220223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Braunsbach |
E1016930
|
entity |
| Predicate | mayorInOfficeSince |
P129568
|
FINISHED |
| Object | 2010 |
—
|
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: 2010 | Statement: [Braunsbach, mayorInOfficeSince, 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayorInOfficeSince Context triple: [Braunsbach, mayorInOfficeSince, 2010]
-
A.
mayorFromYear
chosen
Indicates that an individual holds the position of mayor of a given place starting from a specified year.
-
B.
mayoralTermStart
Indicates the date or point in time when an individual's tenure as mayor officially begins.
-
C.
hasMayorTerm
Indicates that a specified individual holds or has held the office of mayor for a particular jurisdiction during a defined term.
-
D.
currentRepresentativeSince
Indicates the date or time from which an entity has been serving as the current representative of another entity.
-
E.
currentIncumbentStartYear
Indicates the year in which the entity’s current incumbent began their tenure or term in that role.
- 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_69f76de072908190ab65038a8a7b6a79 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78f63c8788190b253a18de5ca1312 |
completed | May 3, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:02 p.m.