Triple
T19788614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berger |
E475344
|
entity |
| Predicate | isCommonInField |
P59663
|
FINISHED |
| Object | politics |
—
|
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: politics | Statement: [Berger, isCommonInField, politics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCommonInField Context triple: [Berger, isCommonInField, politics]
-
A.
inSameFieldAs
Indicates that two entities work, study, or specialize within the same professional or academic field.
-
B.
isCommonInProfession
chosen
Indicates that something frequently occurs, appears, or is typical within a given profession or occupational field.
-
C.
isCommonlyDefinedBy
Indicates that something is typically or most frequently characterized, specified, or described by a particular definition, property, or set of criteria.
-
D.
isCommonAsFirstName
Indicates that the referenced name is frequently used as a first (given) name within a specified population or context.
-
E.
hasCommonValue
Indicates that two or more entities share at least one identical value or attribute in common.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65389c9ac81909e61b3cbb9213e72 |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:49 p.m.