Triple
T37768926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia S30+ |
E941487
|
entity |
| Predicate | typicalDeviceFormFactor |
P9336
|
FINISHED |
| Object | candybar phone |
—
|
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: candybar phone | Statement: [Nokia S30+, typicalDeviceFormFactor, candybar phone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDeviceFormFactor Context triple: [Nokia S30+, typicalDeviceFormFactor, candybar phone]
-
A.
targetFormFactor
Indicates the specific physical configuration or design format that something is intended to be used with or fit into.
-
B.
deviceShape
Indicates that one entity has the physical form or geometric configuration specified by the other entity.
-
C.
hasFormFactor
chosen
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
D.
targetedDeviceType
Indicates the specific type or category of device that is the intended target of an action, configuration, or content.
-
E.
tabletForm
Indicates that something exists or is provided in tablet dosage form.
- 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_69f76ee3251881909bb4451aad50752b |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.