Triple
T16537465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia 1110 |
E401727
|
entity |
| Predicate | smsCapacity |
P123945
|
FINISHED |
| Object | up to 60 messages |
—
|
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: up to 60 messages | Statement: [Nokia 1110, smsCapacity, up to 60 messages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: smsCapacity Context triple: [Nokia 1110, smsCapacity, up to 60 messages]
-
A.
dataCapacityDigits
Indicates the number of decimal digits used to represent or specify a data capacity value.
-
B.
capacityRecord
Indicates a recorded measure of how much of a resource, space, or system is available or can be utilized at a given time.
-
C.
subscriberNumberLengthRange
Indicates the allowed minimum and maximum length range for a subscriber’s phone number in a given context.
-
D.
dataCapacity
Indicates the maximum amount of data that something can store, handle, or transmit.
-
E.
trackCapacity
Indicates the maximum number of trains or amount of traffic that a specific track segment is designed to handle within a given time period.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34559ca948190a9eb810b9b3be079 |
completed | April 18, 2026, 8:48 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:15 a.m.