Triple
T30941825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl von Ossietzky Medal |
E788282
|
entity |
| Predicate | typicalAwardingCity |
P15624
|
FINISHED |
| Object | Berlin |
E5567
|
NE 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: Berlin | Statement: [Carl von Ossietzky Medal, typicalAwardingCity, Berlin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAwardingCity Context triple: [Carl von Ossietzky Medal, typicalAwardingCity, Berlin]
-
A.
awardingCity
Indicates the city in which an award is formally given or conferred.
-
B.
typicalVenueCity
chosen
Indicates that a particular city is the usual or standard location where an event, activity, or organization is typically held or based.
-
C.
typicalAwardedBy
Indicates the usual or standard agent (such as a person or organization) that confers or grants a particular award.
-
D.
awardCity
Indicates the city where an award or prize is formally given or hosted.
-
E.
typicalAwardType
Indicates the usual or most common type or category of award associated with a given entity or context.
- F. None of above.
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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2947012d488190b84641c7ed20e4d0 |
completed | June 10, 2026, 11:14 a.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:53 p.m.