Triple
T8726027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Admiralteyskaya metro station |
E207132
|
entity |
| Predicate | escalatorLength |
P71546
|
FINISHED |
| Object | among the longest in Saint Petersburg Metro |
—
|
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: among the longest in Saint Petersburg Metro | Statement: [Admiralteyskaya metro station, escalatorLength, among the longest in Saint Petersburg Metro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: escalatorLength Context triple: [Admiralteyskaya metro station, escalatorLength, among the longest in Saint Petersburg Metro]
-
A.
escalatorLengthClaim
chosen
Indicates a stated or asserted value for the length of an escalator.
-
B.
hasEscalators
Indicates that one entity is equipped with or contains escalators that can be used for movement between different levels or areas.
-
C.
elevatorTopSpeed_m_per_s
Indicates the maximum speed, in meters per second, that an elevator can travel.
-
D.
numberOfStairs
Indicates the quantity of stairs associated with or present in a given context or structure.
-
E.
hasElevators
Indicates that one entity is equipped with or contains one or more elevators for vertical transportation.
- 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_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. |
Created at: March 30, 2026, 6:36 p.m.