Triple
T1034838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queens Midtown Tunnel |
E22336
|
entity |
| Predicate | hasVentilationBuildings |
P23913
|
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: [Queens Midtown Tunnel, hasVentilationBuildings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVentilationBuildings Context triple: [Queens Midtown Tunnel, hasVentilationBuildings, yes]
-
A.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
B.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
C.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
D.
containsUnionBuildings
Indicates that one entity includes or encompasses buildings associated with a union within its boundaries or composition.
-
E.
isPublicBuilding
Indicates that a building is designated for public use, access, or service rather than being privately owned or restricted.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8d669448190955507e2e4975b9f |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b728ad3481909cf1430349cb9bba |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b8d5076481908640a0d873efdf14 |
completed | March 1, 2026, 10:08 p.m. |
Created at: March 1, 2026, 7:41 p.m.