Triple
T9006268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel Fokine |
E215149
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Firebird |
E217126
|
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: Firebird | Statement: [Michel Fokine, notableWork, Firebird]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Firebird Context triple: [Michel Fokine, notableWork, Firebird]
-
A.
Firebird
Firebird is a floorless steel roller coaster at Six Flags America known for its inversions and smooth, high-speed ride experience.
-
B.
Firebird
chosen
Firebird is a celebrated ballet role, famously performed by Maria Tallchief in Igor Stravinsky’s classic work "The Firebird."
-
C.
Firebird
Firebird is the fiery, mythical bird mascot representing Fremont High School in Sunnyvale, California, symbolizing resilience and school spirit.
-
D.
Firebird
Firebird is an open-source relational database management system known for its support of SQL and cross-platform deployment.
-
E.
Cocoon
Cocoon is a 1985 science fiction comedy-drama film about a group of elderly people who regain youth and vitality after encountering alien life, directed by Ron Howard.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69bc6e208190b0c01e3761c04799 |
completed | April 1, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0e7f090819093c7af51c3979978 |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.