Triple
T18373169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Reid |
E446239
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Radar |
—
|
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: Radar | Statement: [Michael Reid, nickname, Radar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Radar Context triple: [Michael Reid, nickname, Radar]
-
A.
Radar
chosen
Radar is the nickname of American professional golfer Michael Reid, known for his accuracy and steady play on the PGA Tour.
-
B.
Radar
Radar is a character known as one of Lacey Pemberton’s close friends in John Green’s novel "Paper Towns."
-
C.
Radar
Radar is Big Bird’s beloved teddy bear on Sesame Street, often used to comfort him and feature in storylines about friendship and security.
-
D.
Radar Pictures
Radar Pictures is an American film and television production company known for developing and producing a wide range of feature films and series across genres.
-
E.
Bystra radar
Bystra radar is a Polish mobile 3D air-defense radar system designed for detecting and tracking aerial targets at short to medium ranges.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e517561edc8190b5d2834707ab662b |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 10:45 a.m.