Triple
T14286072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Tunnel Tree |
E354178
|
entity |
| Predicate | tunnelUsage |
P91932
|
FINISHED |
| Object | pedestrian passage |
—
|
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: pedestrian passage | Statement: [California Tunnel Tree, tunnelUsage, pedestrian passage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tunnelUsage Context triple: [California Tunnel Tree, tunnelUsage, pedestrian passage]
-
A.
usesTunnel
Indicates that one entity makes use of a tunnel as a passage or route to reach or connect to another entity.
-
B.
tunnelType
Indicates the specific kind or classification of a tunnel associated with an entity.
-
C.
tunnelAllows
chosen
Indicates that a tunnel provides a passage or route that permits movement, access, or flow between two locations or entities.
-
D.
numberOfTunnels
Indicates the quantity of tunnels associated with or passing through a given entity or location.
-
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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de697ef40c8190bea37724b28c2e99 |
completed | April 14, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:11 a.m.