Triple
T9992165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freya-LZ |
E196911
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Freya radar |
E38422
|
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: Freya radar | Statement: [Freya-LZ, basedOn, Freya radar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freya radar Context triple: [Freya-LZ, basedOn, Freya radar]
-
A.
Freya radar
chosen
Freya radar was an early German ground-based radar system used extensively for air defense during World War II.
-
B.
Erieye radar
The Erieye radar is a Swedish airborne early warning and control (AEW&C) radar system known for its active electronically scanned array (AESA) technology and long-range surveillance capabilities.
-
C.
Liana radar
Liana radar is an airborne early warning and control radar system used on the Russian Beriev A-50 aircraft to detect, track, and manage aerial and surface targets.
-
D.
Radar
Radar is the nickname of American professional golfer Michael Reid, known for his accuracy and steady play on the PGA Tour.
-
E.
Radar
Radar is a character known as one of Lacey Pemberton’s close friends in John Green’s novel "Paper Towns."
- 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_69ca82f1678c819093d06320a05f16a4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcb95842c8190b8cdce9584f19840 |
completed | April 2, 2026, 1:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d26a2bc4f081909595afcc2c862eda |
completed | April 5, 2026, 1:56 p.m. |
Created at: March 30, 2026, 8:50 p.m.