Triple
T19782475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atal Tunnel (Rohtang) |
E475171
|
entity |
| Predicate | hasEmergencyTunnel |
P137309
|
FINISHED |
| Object | overhead escape tunnel in the same tube |
—
|
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: overhead escape tunnel in the same tube | Statement: [Atal Tunnel (Rohtang), hasEmergencyTunnel, overhead escape tunnel in the same tube]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyTunnel Context triple: [Atal Tunnel (Rohtang), hasEmergencyTunnel, overhead escape tunnel in the same tube]
-
A.
hasTunnel
Indicates that one entity possesses, contains, or is connected by a tunnel to another entity.
-
B.
usesTunnel
Indicates that one entity makes use of a tunnel as a passage or route to reach or connect to another entity.
-
C.
hasTunnelShape
Indicates that something possesses a form or configuration resembling a tunnel, typically elongated, enclosed, and passage-like.
-
D.
hasDuplexTunnel
Indicates that there exists a bidirectional (two-way) tunnel connection between two entities.
-
E.
hasTunnelSections
Indicates that an entity includes or is composed of multiple distinct tunnel segments or portions.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653852e848190b8971981a164e8f9 |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bcf41c8190b685b5adf46a60fc |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:49 p.m.