Triple
T14759225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A86 motorway |
E346811
|
entity |
| Predicate | hasDuplexTunnel |
P115689
|
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: [A86 motorway, hasDuplexTunnel, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDuplexTunnel Context triple: [A86 motorway, hasDuplexTunnel, yes]
-
A.
hasTunnel
Indicates that one entity possesses, contains, or is connected by a tunnel to another entity.
-
B.
duplexMode
Indicates whether a communication link or device operates in half-duplex or full-duplex mode, defining if data can flow in one or both directions simultaneously.
-
C.
usesDuplexMethod
Indicates that one entity employs a duplex method, meaning a two-way or bidirectional technique or process, in relation to another entity or context.
-
D.
usesTunnel
Indicates that one entity makes use of a tunnel as a passage or route to reach or connect to another entity.
-
E.
hasTunnelShape
Indicates that something possesses a form or configuration resembling a tunnel, typically elongated, enclosed, and passage-like.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f0f5a48190af008352c26574d7 |
completed | April 14, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69de8c02e5c08190943c27594026faf7 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:30 a.m.