Triple
T5219075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berner |
E117823
|
entity |
| Predicate | usedAsNounFor |
P23317
|
FINISHED |
| Object | person from Bern |
—
|
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: person from Bern | Statement: [Berner, usedAsNounFor, person from Bern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsNounFor Context triple: [Berner, usedAsNounFor, person from Bern]
-
A.
isFamouslyUsedIn
Indicates that something is widely recognized or well-known for being used in a particular context, work, or situation.
-
B.
usedAsSuffixTo
Indicates that one entity functions as a suffix appended to another entity, typically to modify or extend its meaning.
-
C.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
D.
nounFormOf
chosen
Indicates that one term is the noun form derived from, or corresponding to, another term (typically a verb or adjective).
-
E.
usedInFullNameOf
Indicates that one entity (such as a word, name part, or title) is used as a component within the complete formal name of another entity.
- 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_69bd4465e03081909bfcfd7113062590 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7ab6e63c8190964b2b65a0206134 |
completed | March 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69bd77bd2a448190a9ae5afd2585a7b9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:48 p.m.