Triple
T2922070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State station |
E78748
|
entity |
| Predicate | isInTunnelSystem |
P43941
|
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: [State station, isInTunnelSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInTunnelSystem Context triple: [State station, isInTunnelSystem, yes]
-
A.
partOfTunnel
Indicates that one entity forms a physical segment or component within the structure or extent of a tunnel.
-
B.
hasTunnel
Indicates that one entity possesses, contains, or is connected by a tunnel to another entity.
-
C.
usesTunnel
Indicates that one entity makes use of a tunnel as a passage or route to reach or connect to another entity.
-
D.
hasUndergroundDepth
Indicates that one entity has a specified vertical extent or depth located below the ground surface relative to another reference or context.
-
E.
hasEntranceOn
Indicates that one entity’s entrance or access point is located on or faces a specified side, boundary, or feature of another entity.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f520208190a4dc43372004555f |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:54 p.m.