Triple
T15252821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Ballhaus |
E364560
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Florian Ballhaus |
E126632
|
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: Florian Ballhaus | Statement: [Michael Ballhaus, child, Florian Ballhaus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Florian Ballhaus Context triple: [Michael Ballhaus, child, Florian Ballhaus]
-
A.
Florian Ballhaus
chosen
Florian Ballhaus is a German cinematographer known for his work on major Hollywood films and television series.
-
B.
Florian Haertel
Florian Haertel is a German journalist and photographer best known as the former husband of British actress Alex Kingston.
-
C.
Andreas Thiel
Andreas Thiel is a notable individual whose identity is associated with the surname Thiel, recognized for achievements that distinguish him among bearers of the name.
-
D.
Stefan Effenberg
Stefan Effenberg is a former German midfielder renowned for his leadership and playmaking at Bayern Munich and the German national team.
-
E.
Andreas Grosch
Andreas Grosch is a film producer best known for his work on the crime drama "Lord of War."
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f728648190b2c86e4528542b65 |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5f390bc8190bc0180c118e1523c |
completed | May 9, 2026, 7:44 a.m. |
Created at: April 10, 2026, 3:13 a.m.