Triple
T3584482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hans |
E75878
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Johan |
E2916
|
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: Johan | Statement: [Hans, relatedName, Johan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johan Context triple: [Hans, relatedName, Johan]
-
A.
Johan
chosen
Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
-
B.
Johanus
Johanus is a given name, likely a variant or diminutive of Johan, used as a personal first name in some cultures.
-
C.
Johann
Johann is a given name of Germanic origin commonly used in German-speaking and other European countries.
-
D.
Johan Evertsen
Johan Evertsen was a prominent 17th-century Dutch admiral who played a key role in the naval conflicts of the Dutch Republic, including the Anglo-Dutch Wars.
-
E.
Morten
Morten is a masculine given name commonly used in Scandinavian countries, derived from the Latin name Martinus.
- 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_69ad85d6dc3c8190b491b79b83e25461 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc10f9b508190bde4a4e4711dd452 |
completed | March 8, 2026, 6:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4882803e481908bc716c8beda3c73 |
completed | March 13, 2026, 9:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.