Triple
T19648528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel Gill |
E471743
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Condor |
—
|
NE NERFINISHED |
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: Condor | Statement: [Michel Gill, notableWork, Condor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Condor Context triple: [Michel Gill, notableWork, Condor]
-
A.
Condor
Condor is a German leisure airline known for operating holiday flights to popular vacation destinations, primarily from bases in Germany.
-
B.
Condor
chosen
Condor is the codename of the CIA analyst protagonist in the political thriller novel and film "Three Days of the Condor."
-
C.
Condor
Condor is the surname of actress Lana Condor, best known for her lead role in the "To All the Boys I've Loved Before" film series.
-
D.
Condor
Condor is the nickname of the Focke-Wulf Fw 200, a long-range German airliner later used as a maritime patrol and bomber aircraft during World War II.
-
E.
Condors
Condors is the nickname of the Bakersfield Condors, a professional ice hockey team based in Bakersfield, California.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64126cea88190a1a6929f46de4686 |
completed | April 20, 2026, 3:07 p.m. |
Created at: April 10, 2026, 1:44 p.m.