Triple
T14902568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hendrika |
E360042
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Hennie |
E837756
|
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: Hennie | Statement: [Hendrika, hasDiminutive, Hennie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hennie Context triple: [Hendrika, hasDiminutive, Hennie]
-
A.
Hennie
chosen
Hennie is a Norwegian surname most notably associated with actor and director Aksel Hennie.
-
B.
Hennie Berger
Hennie Berger is a central character in Clifford Odets' play "Awake and Sing!", representing the struggles and aspirations of a young woman in a working-class Jewish family during the Great Depression.
-
C.
Rudi Theron
Rudi Theron is a person notable enough to be recognized as a namesake or prominent individual associated with the surname Theron.
-
D.
Johan Theron
Johan Theron is a South African former professional tennis player who competed primarily on the ITF Futures and ATP Challenger circuits.
-
E.
Alan Durband
Alan Durband was a British teacher, writer, and influential drama educator from Liverpool, known for his popular guides to Shakespeare and his impact on English education.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded60b24008190bd272c0d61329400 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e83418081908280a9ed8ddb9fd7 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 2:11 a.m.