Triple
T3381427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afrikanische Straße |
E71192
|
entity |
| Predicate | hasStationStructure |
P47116
|
FINISHED |
| Object | underground |
—
|
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: underground | Statement: [Afrikanische Straße, hasStationStructure, underground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationStructure Context triple: [Afrikanische Straße, hasStationStructure, underground]
-
A.
hasStationBuilding
Indicates that a station is associated with or includes a station building as part of its facilities.
-
B.
hasStationGroup
Indicates that an entity is associated with, or belongs to, a particular group or collection of stations.
-
C.
hasComponentStation
Indicates that an entity includes or is associated with a specific station as one of its component parts.
-
D.
hasStationCode
Indicates that an entity is associated with a specific station identification code.
-
E.
hasStationBuildingMaterial
Indicates that a station’s building is constructed from, or primarily composed of, a specified material.
- 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_69ad85a8fd9c819095ecedf838d2bf1b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb5e9af608190bfb228ef99a87bb7 |
completed | March 8, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69ada434bae48190a77ea37f9274ad8f |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada527ff308190813a7ffdcdec4322 |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:14 p.m.