Triple
T8871575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Fe de Antioquia |
E211167
|
entity |
| Predicate | WestTunnelInstanceOf |
P85457
|
FINISHED |
| Object | road tunnel |
—
|
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: road tunnel | Statement: [Santa Fe de Antioquia, WestTunnelInstanceOf, road tunnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WestTunnelInstanceOf Context triple: [Santa Fe de Antioquia, WestTunnelInstanceOf, road tunnel]
-
A.
hasRailwayTunnel
Indicates that one entity contains, includes, or is connected by a railway tunnel associated with the other entity.
-
B.
SeikanTunnelType
Indicates that one entity is classified as a specific type or category of Seikan Tunnel.
-
C.
partOfTunnel
Indicates that one entity forms a physical segment or component within the structure or extent of a tunnel.
-
D.
hasBridgeTunnel
Indicates that there exists a bridge or tunnel connection between two locations or structures.
-
E.
hasSubseaTunnel
Indicates that one location or structure is connected to another by an underwater tunnel.
- 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_69ca838d3c7c8190a849566d5afd2b11 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61281e888190a32b08980310979f |
completed | April 1, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2956788190a311c647b4da17a6 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5d6e54808190af4156edd4c8ffbc |
completed | March 31, 2026, 11:49 p.m. |
Created at: March 30, 2026, 6:51 p.m.