Triple
T8714991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munich S-Bahn trunk line |
E206870
|
entity |
| Predicate | cityCentreSection |
P80700
|
FINISHED |
| Object | mostly 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: mostly underground | Statement: [Munich S-Bahn trunk line, cityCentreSection, mostly underground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityCentreSection Context triple: [Munich S-Bahn trunk line, cityCentreSection, mostly underground]
-
A.
hasCityCentreLocation
Indicates that something is located in, or directly associated with, the central area of a city.
-
B.
notableCityCenter
Indicates that a location serves as a prominent or significant central area within a city.
-
C.
isUrbanSectionOf
chosen
Indicates that one area or segment is the part of a larger entity that lies within an urban or city environment.
-
D.
centralLocation
Indicates that one entity serves as the primary or central place associated with another entity.
-
E.
citySide
Indicates that one entity is located on or along a particular side or edge of a city relative to another reference point.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd6707c819092c9fca34f273d5e |
completed | March 31, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:35 p.m.