Triple
T1455480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lincoln Tunnel |
E31386
|
entity |
| Predicate | hasVentilationSystem |
P6655
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lincoln Tunnel, hasVentilationSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVentilationSystem Context triple: [Lincoln Tunnel, hasVentilationSystem, yes]
-
A.
hasVentilationBuildings
Indicates that certain buildings are designated to provide ventilation for another structure, area, or system.
-
B.
airIntakeType
Indicates the type or configuration of the system or mechanism used to draw air into an engine or device.
-
C.
airIntakeLocation
Indicates the physical position or area where air is drawn into a system, device, or structure.
-
D.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
-
E.
hasInteriorFeature
chosen
Indicates that an entity contains or includes a specific feature within its interior space.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c581714881909bf4c2bad9645176 |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47cdbd0819092022344a2f4ad7b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.