Triple
T12515690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twofish |
E299185
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Blowfish |
E845867
|
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: Blowfish | Statement: [Twofish, relatedTo, Blowfish]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blowfish Context triple: [Twofish, relatedTo, Blowfish]
-
A.
Blowfish
chosen
Blowfish is a symmetric-key block cipher designed by Bruce Schneier, known for its speed and simplicity, and widely used in various encryption applications.
-
B.
Firebird
Firebird is the fiery, mythical bird mascot representing Fremont High School in Sunnyvale, California, symbolizing resilience and school spirit.
-
C.
Firebird
Firebird is an open-source relational database management system known for its support of SQL and cross-platform deployment.
-
D.
Firebird
Firebird is a Marvel Comics superheroine with pyrokinetic powers who has been affiliated with teams like the Avengers and the Rangers.
-
E.
Firebird
Firebird is a floorless steel roller coaster at Six Flags America known for its inversions and smooth, high-speed ride experience.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541f80148190976d1d912fe155d0 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f655745cec8190b5582eb4a339d501 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.