Triple
T30701677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tempelhof Town Hall |
E781625
|
entity |
| Predicate | isLocatedInFederalState |
P174787
|
FINISHED |
| Object | Berlin (state) |
—
|
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: Berlin (state) | Statement: [Tempelhof Town Hall, isLocatedInFederalState, Berlin (state)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLocatedInFederalState Context triple: [Tempelhof Town Hall, isLocatedInFederalState, Berlin (state)]
-
A.
federalStateOfGermany
Indicates that one entity is a federal state (Bundesland) that is a constituent state within the country of Germany.
-
B.
federalStateCode
Indicates that an entity is associated with, governed by, or identified through a specific federal state code within a country’s administrative or legal system.
-
C.
federalStateName
Indicates that an entity has the name of a federal state (such as a state, province, or similar first-level administrative division).
-
D.
isInBundesland
chosen
Indicates that one entity (typically a place or city) is located within a specific German federal state (Bundesland).
-
E.
isLocatedInFranconiaRegion
Indicates that something is situated within the geographical boundaries of the Franconia region.
- 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_69f224abfcf081909492e64d3cc35262 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: April 29, 2026, 8:34 p.m.