Triple
T2326905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rick Blaine |
E48307
|
entity |
| Predicate | employerOf |
P7
|
FINISHED |
| Object | Sascha |
unclear NED1
|
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: Sascha | Statement: [Rick Blaine, employerOf, Sascha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sascha Context triple: [Rick Blaine, employerOf, Sascha]
-
A.
Sasha
Sasha is a common Russian diminutive form of the given name Alexander (and also Alexandra).
-
B.
Sasha
Sasha is one of the costumed cougar mascots representing the University of Houston's athletic teams, the Houston Cougars.
-
C.
Markus
Markus is the given first name of the renowned abstract expressionist painter Mark Rothko.
-
D.
Lukas
Lukas is a masculine given name commonly used in various European countries, often associated with the biblical name Luke.
-
E.
Sven
Sven is the lovable reindeer companion in Disney's animated film "Frozen," known for his close bond with Kristoff and his expressive, dog-like personality.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc64b62a08190b5a415769ce42645 |
completed | March 7, 2026, 6:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae9615f000819092f9dc4700998b25 |
completed | March 9, 2026, 9:42 a.m. |
Created at: March 4, 2026, 7:50 p.m.