Triple
T7913191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erich |
E183749
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object | Erik |
E167663
|
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: Erik | Statement: [Erich, hasShortForm, Erik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erik Context triple: [Erich, hasShortForm, Erik]
-
A.
Erik
chosen
Erik is a masculine given name of Scandinavian origin that is widely used across various European countries.
-
B.
Erikli
Erikli is a Turkish bottled water brand known for its natural spring water, marketed under the Nestlé Waters portfolio.
-
C.
Erik Neander
Erik Neander is a Major League Baseball executive known for leading the Tampa Bay Rays’ front office and overseeing the club’s baseball operations and roster construction.
-
D.
Mikael
Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
-
E.
Henrik
Henrik is the given name of the renowned Norwegian mathematician Niels Henrik Abel, known for his pioneering work in algebra and analysis.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a748f4c8190bcd868de2fcf0b3a |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdff156c481909a32be8828f407ad |
completed | March 31, 2026, 2:53 p.m. |
Created at: March 30, 2026, 5:04 p.m.