Triple
T33867431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington/Dearborn |
E868095
|
entity |
| Predicate | locatedInTunnelUnder |
P43941
|
FINISHED |
| Object | Dearborn Street Subway |
E92000
|
NE 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: Dearborn Street Subway | Statement: [Washington/Dearborn, locatedInTunnelUnder, Dearborn Street Subway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInTunnelUnder Context triple: [Washington/Dearborn, locatedInTunnelUnder, Dearborn Street Subway]
-
A.
isInTunnelSystem
chosen
Indicates that one entity is located within or forms part of a tunnel system associated with another entity.
-
B.
partOfTunnel
Indicates that one entity forms a physical segment or component within the structure or extent of a tunnel.
-
C.
tunnelLocation
Indicates that one entity is the location or site where a tunnel is situated or passes through in relation 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.
hasRailwayTunnel
Indicates that one entity contains, includes, or is connected by a railway tunnel associated with the other entity.
- F. None of above.
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_69f34995029081909ede0f7df73d1a5e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3682343e3c81909bc0e5903660222a |
completed | June 20, 2026, 12:06 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:47 a.m.