Triple
T11317287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evpatoria planetary radar |
E267998
|
entity |
| Predicate | hasAntenna |
P21286
|
FINISHED |
| Object |
RT-70
RT-70 is a large, 70-meter radio telescope antenna used for deep-space communication and radar astronomy at the Evpatoria planetary radar facility.
|
E918819
|
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: RT-70 | Statement: [Evpatoria planetary radar, hasAntenna, RT-70]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RT-70 Context triple: [Evpatoria planetary radar, hasAntenna, RT-70]
-
A.
R70
R70 is a London bus route that provides public transport connections to and from Hampton and surrounding areas.
-
B.
R7
R7 is a commuter rail line within the Rodalies de Catalunya network serving the Barcelona metropolitan area in Catalonia, Spain.
-
C.
J70
The J70 is a long-running generation of the Toyota Land Cruiser renowned for its rugged body-on-frame construction, off-road durability, and continued use in demanding commercial and remote-area applications worldwide.
-
D.
E70
E70 is BMW's internal model designation for the second-generation X5 mid-size luxury SUV produced from 2006 to 2013.
-
E.
M-77
M-77 is a state highway in Michigan, United States, running north–south through the eastern Upper Peninsula.
- 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: RT-70 Triple: [Evpatoria planetary radar, hasAntenna, RT-70]
Generated description
RT-70 is a large, 70-meter radio telescope antenna used for deep-space communication and radar astronomy at the Evpatoria planetary radar facility.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RT-70 Target entity description: RT-70 is a large, 70-meter radio telescope antenna used for deep-space communication and radar astronomy at the Evpatoria planetary radar facility.
-
A.
R70
R70 is a London bus route that provides public transport connections to and from Hampton and surrounding areas.
-
B.
R7
R7 is a commuter rail line within the Rodalies de Catalunya network serving the Barcelona metropolitan area in Catalonia, Spain.
-
C.
J70
The J70 is a long-running generation of the Toyota Land Cruiser renowned for its rugged body-on-frame construction, off-road durability, and continued use in demanding commercial and remote-area applications worldwide.
-
D.
E70
E70 is BMW's internal model designation for the second-generation X5 mid-size luxury SUV produced from 2006 to 2013.
-
E.
M-77
M-77 is a state highway in Michigan, United States, running north–south through the eastern Upper Peninsula.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c3cf748190987838029d9f7fff |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e525d3160c8190b58c5c04a66b3e3e |
completed | April 19, 2026, 6:58 p.m. |
| NEDg | Description generation | batch_69e52c81449c8190847b64fa91a45b2e |
completed | April 19, 2026, 7:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e531b079708190ac9e19127d36a848 |
completed | April 19, 2026, 7:49 p.m. |
Created at: April 8, 2026, 9:32 p.m.