Triple
T8726032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Admiralteyskaya metro station |
E207132
|
entity |
| Predicate | hasUndergroundVestibule |
P84284
|
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: [Admiralteyskaya metro station, hasUndergroundVestibule, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUndergroundVestibule Context triple: [Admiralteyskaya metro station, hasUndergroundVestibule, yes]
-
A.
hasUndergroundSection
Indicates that an entity includes a portion or segment that is located below ground level.
-
B.
hasUndergroundFacilities
Indicates that one entity possesses or contains facilities or infrastructure located below ground level in relation to another entity.
-
C.
hasUndergroundDepth
Indicates that one entity has a specified vertical extent or depth located below the ground surface relative to another reference or context.
-
D.
isUndergroundOnly
Indicates that something exists, operates, or is accessible exclusively below ground level and not above ground.
-
E.
hasLowerFloor
Indicates that one location, structure, or level includes or is directly connected to a floor situated below another floor.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d158b0481908249610458f97306 |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc489dd528819084ed5d88bd8bb3d6 |
completed | March 31, 2026, 10:20 p.m. |
Created at: March 30, 2026, 6:36 p.m.