Triple
T6673062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unter den Linden U-Bahn station |
E151778
|
entity |
| Predicate | locatedNearGovernmentDistrict |
P72400
|
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: [Unter den Linden U-Bahn station, locatedNearGovernmentDistrict, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedNearGovernmentDistrict Context triple: [Unter den Linden U-Bahn station, locatedNearGovernmentDistrict, true]
-
A.
basedInDistrict
Indicates that an entity is located or has its primary base of operations within a specific administrative district.
-
B.
governmentDistrict
Indicates that a government entity has jurisdiction over or is administratively associated with a specific district.
-
C.
locatedNearUnionTerritory
Indicates that one entity is geographically situated close to, or in the immediate vicinity of, a Union Territory.
-
D.
locatedNearPass
Indicates that one entity is situated close to a mountain pass or similar passageway.
-
E.
containsDistrictMunicipality
Indicates that an administrative region includes one or more district municipalities within its boundaries.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
| PDg | Predicate description generation | batch_69c6ce72809c8190be85f6e42ca1c8ea |
completed | March 27, 2026, 6:37 p.m. |
Created at: March 27, 2026, 2:03 p.m.