Triple
T10738456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heike |
E253255
|
entity |
| Predicate | shortFormOf |
P43
|
FINISHED |
| Object | Henrike |
E352030
|
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: Henrike | Statement: [Heike, shortFormOf, Henrike]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henrike Context triple: [Heike, shortFormOf, Henrike]
-
A.
Henrike
chosen
Henrike is a feminine given name of German origin, serving as the female form of Heinrich.
-
B.
Ulrike
Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
-
C.
Edvarda
Edvarda is a central fictional character in Knut Hamsun’s novel "Pan," known for her complex and tumultuous relationship with the protagonist.
-
D.
Ulrika
Ulrika is a central character in the Swedish musical "Kristina från Duvemåla," known as a strong-willed and controversial woman whose life intertwines with the emigrant community.
-
E.
Ingeborg
Ingeborg is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710424d8c81908ee9b59d622f2af5 |
completed | April 9, 2026, 2:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de558f26e88190a9cb8f4d0539e5a5 |
completed | April 14, 2026, 2:56 p.m. |
Created at: April 8, 2026, 9:14 p.m.