Triple
T26364065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin U-Bahn line U2 |
E660283
|
entity |
| Predicate | connectsKeyCentralDistricts |
P101470
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Berlin U-Bahn line U2, connectsKeyCentralDistricts, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsKeyCentralDistricts Context triple: [Berlin U-Bahn line U2, connectsKeyCentralDistricts, true]
-
A.
connectsKeyDistrict
chosen
Indicates that one entity establishes or maintains a significant linkage or route to a strategically important or central district.
-
B.
connectsCentralDistrictsWith
Indicates a relationship where something serves as a link or route joining central districts to one another.
-
C.
connectsCentralAreaTo
Indicates a relationship where one element serves as a link or pathway between a central area and another location or component.
-
D.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
E.
connectsMunicipalities
Indicates a relationship where one entity serves as a link or route that joins two or more municipalities.
- 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_69ee8126d52c8190bc0b34337c2c9aa8 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 26, 2026, 10:53 p.m.