Triple
T12756372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City and South London Railway |
E304869
|
entity |
| Predicate | tunnelShape |
P63747
|
FINISHED |
| Object | circular cast-iron tube |
—
|
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: circular cast-iron tube | Statement: [City and South London Railway, tunnelShape, circular cast-iron tube]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tunnelShape Context triple: [City and South London Railway, tunnelShape, circular cast-iron tube]
-
A.
hasTunnelShape
chosen
Indicates that something possesses a form or configuration resembling a tunnel, typically elongated, enclosed, and passage-like.
-
B.
tunnelType
Indicates the specific kind or classification of a tunnel associated with an entity.
-
C.
tunnelCircumference
Indicates the circular distance around the inner boundary of a tunnel’s cross-section.
-
D.
partOfTunnel
Indicates that one entity forms a physical segment or component within the structure or extent of a tunnel.
-
E.
tunnels
Indicates that one entity passes through, under, or within another entity via a tunnel-like passage or structure.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8b57b88190b29b8fdca415c81c |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:27 p.m.