Triple
T3883815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becker Professional Education |
E92889
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | Becker |
E115890
|
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: Becker | Statement: [Becker Professional Education, hasAbbreviation, Becker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Becker Context triple: [Becker Professional Education, hasAbbreviation, Becker]
-
A.
Becker
chosen
Becker is a surname of German origin, commonly associated with individuals in German-speaking countries and their descendants worldwide.
-
B.
Bek
Bek is a short or informal given name, typically used as a diminutive of Rebekah.
-
C.
Beckmann
Beckmann is a German surname most famously associated with the Expressionist painter Max Beckmann.
-
D.
Becks
Becks is a popular German beer brand, formally known as Beck's, recognized worldwide for its pilsner-style lager.
-
E.
Eberstein
Eberstein is a German surname most notably associated with August Eberstein, a co-founder of the Montblanc pen company.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeec9029908190a7b36a3827734db1 |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b512594fa081909ba2afad11f6ea59 |
completed | March 14, 2026, 7:46 a.m. |
Created at: March 9, 2026, 3:20 p.m.