Triple
T31781708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grafrath |
E811217
|
entity |
| Predicate | federalStateCapitalNearby |
P173779
|
FINISHED |
| Object | Munich |
—
|
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: Munich | Statement: [Grafrath, federalStateCapitalNearby, Munich]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: federalStateCapitalNearby Context triple: [Grafrath, federalStateCapitalNearby, Munich]
-
A.
regionCapitalNearby
Indicates that a capital city of a region is located close to the referenced place or entity.
-
B.
countyCapitalNearby
Indicates that a county’s capital city is located close to a specified place or entity.
-
C.
countryCapitalNearby
Indicates that a country’s capital city is geographically close to a specified location or entity.
-
D.
capitalOfProvinceNearby
Indicates that a city serves as the capital of a province that is geographically close to a specified reference location or area.
-
E.
nearbyTraditionalCapital
Indicates that one location is geographically close to a place that serves or served as a traditional capital.
- F. None of above. chosen
Provenance (4 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_69f348e544a48190ab6e700b05f6438c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ba1733408190af579d93a7946508 |
completed | May 3, 2026, 2:59 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b960ca4081909a77690c2b122f5e |
completed | May 3, 2026, 2:56 a.m. |
Created at: April 30, 2026, 11:36 p.m.