Triple
T24925133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin Gesundbrunnen station |
E618832
|
entity |
| Predicate | DS100Code |
P157239
|
FINISHED |
| Object | BGS |
—
|
NE NERFINISHED |
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: BGS | Statement: [Berlin Gesundbrunnen station, DS100Code, BGS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: DS100Code Context triple: [Berlin Gesundbrunnen station, DS100Code, BGS]
-
A.
designCode
Indicates that one entity creates, specifies, or defines the design or coding scheme used by another entity.
-
B.
MOSCode
Indicates a relationship where a specific Military Occupational Specialty (MOS) code is assigned to or associated with an entity, such as a person, position, or role.
-
C.
statisticsCode
Indicates that an entity is associated with a specific statistics-related code used for classification, reporting, or analysis.
-
D.
campusCode
Indicates the specific campus identifier associated with an entity, typically distinguishing which campus a person, program, or resource belongs to.
-
E.
codingDomain
Indicates that an entity operates within, pertains to, or is characterized by a particular domain or field of coding or programming.
- 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_69e2fab9edd88190b86004a78a28bc20 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f423afd1ec8190a7660bc5174f49db |
completed | May 1, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69f4210130d08190ae30b7943f7a0bbc |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f423637bec8190a1701421ac86a3b7 |
completed | May 1, 2026, 3:52 a.m. |
Created at: April 18, 2026, 5:29 a.m.