Triple
T24998441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HOB–WTC |
E625640
|
entity |
| Predicate | operatesInTunnel |
P18707
|
FINISHED |
| Object | under the Hudson River |
—
|
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: under the Hudson River | Statement: [HOB–WTC, operatesInTunnel, under the Hudson River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesInTunnel Context triple: [HOB–WTC, operatesInTunnel, under the Hudson River]
-
A.
canOperateInTunnels
Indicates that the subject has the capability or is permitted to function or be used within tunnel environments.
-
B.
tunnelOperationMode
Indicates the specific operational state or mode in which a tunnel system or tunnel-related process is currently functioning.
-
C.
usesTunnel
chosen
Indicates that one entity makes use of a tunnel as a passage or route to reach or connect to another entity.
-
D.
tunnelUse
Indicates that one entity makes use of or passes through a tunnel associated with another entity.
-
E.
tunnelType
Indicates the specific kind or classification of a tunnel associated with an entity.
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f69383222c81909d8baa04129d5c81 |
completed | May 3, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 18, 2026, 6:04 a.m.