Triple
T5084808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betzdorf, Luxembourg |
E114610
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Berg |
E492126
|
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: Berg | Statement: [Betzdorf, Luxembourg, contains, Berg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berg Context triple: [Betzdorf, Luxembourg, contains, Berg]
-
A.
Berg
Berg was a historical German territorial entity that gave its name to the later Grand Duchy of Berg in the Rhineland region.
-
B.
Berg
chosen
Berg is a small town in eastern Luxembourg that serves as the administrative center of the commune of Betzdorf.
-
C.
Wilseder Berg
Wilseder Berg is a prominent hill and popular viewpoint in northern Germany, known for its scenic heathland landscapes within the Lüneburg Heath region.
-
D.
Hoche
Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
-
E.
Gora
Gora is a major Bengali novel by Rabindranath Tagore that explores themes of identity, nationalism, and religious and social reform in colonial India.
- 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_69bd443e941881908eb4e8c685b6f656 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75192d188190a7631bce5faf7de3 |
completed | March 20, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba6f3eb48190b544bf743829cb0c |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:40 p.m.