Triple
T32937984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medical Center station |
E842583
|
entity |
| Predicate | pedestrianTunnelConnects |
P124479
|
FINISHED |
| Object | NIH campus |
—
|
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: NIH campus | Statement: [Medical Center station, pedestrianTunnelConnects, NIH campus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pedestrianTunnelConnects Context triple: [Medical Center station, pedestrianTunnelConnects, NIH campus]
-
A.
ropewayConnects
Indicates that a ropeway (such as a cable car or gondola system) provides a direct transportation connection between two locations.
-
B.
hasPedestrianAccessTo
Indicates that a location or area can be reached or entered safely and directly by people on foot.
-
C.
passagewayConnection
chosen
Indicates a relationship where one passageway provides a direct route or link between two locations or spaces.
-
D.
hasSeparateBicycleTunnel
Indicates that a roadway or route includes a distinct, dedicated tunnel specifically for bicycle traffic, separate from tunnels used by other modes of transport.
-
E.
hasSubwayOrUnderpass
Indicates that there exists a subway or underpass connecting or located at the related entities.
- 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_69f34949727c81909d195c97de3341c8 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d10d78d08190a7e0f6ed3b827322 |
completed | May 3, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe5f93c8190995c53dbbe380a32 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:20 a.m.