Triple
T4381574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merkle |
E99141
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Merkel |
E805
|
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: Merkel | Statement: [Merkle, hasVariant, Merkel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merkel Context triple: [Merkle, hasVariant, Merkel]
-
A.
Angela Merkel
chosen
Angela Merkel is a German politician who served as Chancellor of Germany from 2005 to 2021 and became one of the most influential leaders in Europe and the world.
-
B.
Hannelore Kohl
Hannelore Kohl was a German translator and the longtime wife of former Chancellor Helmut Kohl, known for her public role during his tenure and her later struggles with a debilitating light allergy.
-
C.
Frank-Walter Steinmeier
Frank-Walter Steinmeier is a German politician and diplomat who has served as the President of Germany since 2017 and was previously the country’s foreign minister.
-
D.
Frau Bundeskanzlerin
Frau Bundeskanzlerin is the formal German mode of address used for a woman serving as the Federal Chancellor of Germany.
-
E.
Steinbrueck
Steinbrueck is a surname most notably associated with Victor Steinbrueck, an influential American architect and preservationist known for helping save Seattle’s Pike Place Market.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352613dd481909e008a8db239a108 |
completed | March 12, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e51ff9188190aa4581d451feaafd |
completed | March 14, 2026, 10:45 p.m. |
Created at: March 12, 2026, 11:18 p.m.