Triple
T1049566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsche Bahn |
E22662
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | DB |
E119081
|
NE 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: DB | Statement: [Deutsche Bahn, hasAbbreviation, DB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Context triple: [Deutsche Bahn, hasAbbreviation, DB]
-
A.
DB
chosen
DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
-
B.
DBE
DBE is the title "Dame Commander of the Order of the British Empire," a high-ranking honor awarded in the British honours system.
-
C.
SQL
SQL (Structured Query Language) is a standardized programming language used to manage, query, and manipulate data in relational database management systems.
-
D.
RDS
RDS is a Canadian French-language sports television network that broadcasts a wide range of professional and amateur sporting events.
-
E.
MariaDB
MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b2c6208190b6fdf3e93b1b1d04 |
completed | March 1, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac429cc3c481909c55459790d6857f |
completed | March 7, 2026, 3:22 p.m. |
Created at: March 1, 2026, 7:42 p.m.