Triple
T19592795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carillon Berlin |
E470276
|
entity |
| Predicate | isNonElectronic |
P136387
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Carillon Berlin, isNonElectronic, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNonElectronic Context triple: [Carillon Berlin, isNonElectronic, true]
-
A.
isMechanicalOrElectronic
Indicates that something operates using mechanical components, electronic components, or a combination of both.
-
B.
notPhysicalCash
Indicates that the transaction, payment, or value transfer does not involve tangible paper money or coins, but instead uses non-cash forms such as digital, electronic, or other non-physical means.
-
C.
isNonFoodProduct
Indicates that the referenced item is classified as a product that is not intended for consumption as food.
-
D.
isNonJudicial
Indicates that an action, process, or decision occurs outside of formal judicial proceedings and is not carried out by a court or judge.
-
E.
hasElectronicCharacter
Indicates that something possesses qualities, properties, or behavior associated with electronics or electronic systems.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64057460c8190962e2e58f06b3985 |
completed | April 20, 2026, 3:03 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
| PDg | Predicate description generation | batch_69e5174b060c81908937ff9ff7fce611 |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 1:43 p.m.