Triple
T30350691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony WI-C310 |
E771980
|
entity |
| Predicate | hasInLineRemote |
P198288
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Sony WI-C310, hasInLineRemote, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInLineRemote Context triple: [Sony WI-C310, hasInLineRemote, yes]
-
A.
hasDeFactoLine
Indicates that there exists an unofficial or non-legally recognized boundary or demarcation line functioning in practice between the related entities.
-
B.
isInRemoteArea
Indicates that an entity is located in a geographically isolated or sparsely populated area, typically far from urban centers or standard infrastructure.
-
C.
hasKeyLine
Indicates that one entity serves as the primary or central reference line for another entity, often used as a main axis or defining guideline.
-
D.
hasNearbyLine
Indicates that one entity is located close to, or in the vicinity of, a particular line or linear feature.
-
E.
containsLine
Indicates that one entity includes or encloses a specific line within its spatial or structural extent.
- 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_69f2248b9a208190bc3e6804acd5afd6 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fed83b1d188190a318b0ad3003200a |
completed | May 9, 2026, 6:46 a.m. |
| PD | Predicate disambiguation | batch_69fed78e03548190b6e6ad93ae8d131d |
completed | May 9, 2026, 6:43 a.m. |
| PDg | Predicate description generation | batch_69fed83a3b8c819092a3bd1ca9d9b38b |
completed | May 9, 2026, 6:46 a.m. |
Created at: April 29, 2026, 7:56 p.m.