Triple
T35364774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eggesin |
E1021598
|
entity |
| Predicate | isBorderRegionTown |
P28598
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Eggesin, isBorderRegionTown, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBorderRegionTown Context triple: [Eggesin, isBorderRegionTown, true]
-
A.
isBorderDistrict
Indicates that a district is located along and directly borders the boundary of a larger administrative region or country.
-
B.
isBorderMunicipality
chosen
Indicates that a municipality is located on or directly adjacent to the border of a larger administrative region, country, or jurisdiction.
-
C.
isBorderTownBetween
Indicates that a town is located on or near the boundary separating two specified regions, serving as a border settlement between them.
-
D.
isInBorderTown
Indicates that an entity is located in a town situated on or very near a political or geographic border.
-
E.
hasBorderTownRole
Indicates that an entity serves in an official capacity or role specifically related to a town located on or near a border.
- 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_69f76def44c881908a20e8008572eb44 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.