Triple
T16353393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PIT-RADWAR |
E397112
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object |
Soła radar
The Soła radar is a Polish mobile three-dimensional surveillance radar system designed for short-range air defense and battlefield reconnaissance.
|
E1208779
|
NE FINISHED |
How this triple was built (4 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: Soła radar | Statement: [PIT-RADWAR, product, Soła radar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soła radar Context triple: [PIT-RADWAR, product, Soła radar]
-
A.
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.
-
B.
Radar
Radar is the nickname of American professional golfer Michael Reid, known for his accuracy and steady play on the PGA Tour.
-
C.
Radar
Radar is a character known as one of Lacey Pemberton’s close friends in John Green’s novel "Paper Towns."
-
D.
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.
-
E.
Freya radar
Freya radar was an early German ground-based radar system used extensively for air defense during World War II.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Soła radar Triple: [PIT-RADWAR, product, Soła radar]
Generated description
The Soła radar is a Polish mobile three-dimensional surveillance radar system designed for short-range air defense and battlefield reconnaissance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Soła radar Target entity description: The Soła radar is a Polish mobile three-dimensional surveillance radar system designed for short-range air defense and battlefield reconnaissance.
-
A.
Radar
Radar is a character known as one of Lacey Pemberton’s close friends in John Green’s novel "Paper Towns."
-
B.
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.
-
C.
Radar
Radar is the nickname of American professional golfer Michael Reid, known for his accuracy and steady play on the PGA Tour.
-
D.
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.
-
E.
Freya radar
Freya radar was an early German ground-based radar system used extensively for air defense during World War II.
- F. None of above. chosen
Provenance (5 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2faccab748190b11e0808e422f2ea |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002db841dc8190bfe8a0d8fca1b309 |
completed | May 10, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_6a002f46da5c81909c6e726fe89a3f81 |
completed | May 10, 2026, 7:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a003063fd748190ba42c55b008202fc |
completed | May 10, 2026, 7:14 a.m. |
Created at: April 10, 2026, 5:07 a.m.