Triple
T11141787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Świętokrzyska metro station |
E263570
|
entity |
| Predicate | hasUndergroundLevel |
P98017
|
FINISHED |
| Object | multiple levels |
—
|
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: multiple levels | Statement: [Świętokrzyska metro station, hasUndergroundLevel, multiple levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUndergroundLevel Context triple: [Świętokrzyska metro station, hasUndergroundLevel, multiple levels]
-
A.
hasUndergroundSection
Indicates that an entity includes a portion or segment that is located below ground level.
-
B.
hasUndergroundDepth
Indicates that one entity has a specified vertical extent or depth located below the ground surface relative to another reference or context.
-
C.
hasUndergroundFacilities
Indicates that one entity possesses or contains facilities or infrastructure located below ground level in relation to another entity.
-
D.
hasUndergroundVestibule
Indicates that one entity possesses or includes an underground vestibule space connected to it.
-
E.
hasUndergroundConnections
Indicates that one entity is linked to another through subterranean or hidden passageways, networks, or channels.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8623158819096ad1678fa9e72bb |
completed | April 9, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d7706116248190a87440bec3960884 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:28 p.m.