Triple
T26153822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Thameslink network |
E659900
|
entity |
| Predicate | hasCoreTunnels |
P21069
|
FINISHED |
| Object | Snow Hill tunnel |
—
|
NE NERFINISHED |
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: Snow Hill tunnel | Statement: [London Thameslink network, hasCoreTunnels, Snow Hill tunnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoreTunnels Context triple: [London Thameslink network, hasCoreTunnels, Snow Hill tunnel]
-
A.
hasTunnel
chosen
Indicates that one entity possesses, contains, or is connected by a tunnel to another entity.
-
B.
hasTunnelStubs
Indicates that one entity possesses or includes incomplete or partial tunnel segments that connect or are intended to connect to another structure or system.
-
C.
hasTunnelFunction
Indicates that one entity serves as a tunnel or provides a tunneling function for another entity.
-
D.
hasTunnelSections
Indicates that an entity includes or is composed of multiple distinct tunnel segments or portions.
-
E.
hasEmergencyTunnel
Indicates that one location, structure, or system possesses a dedicated emergency tunnel connecting it to another place or route for use in urgent or hazardous situations.
- 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_69ee5bc5a9908190899d39ce95c6d215 |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
Created at: April 26, 2026, 8:26 p.m.