Triple
T37105126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RT-70 |
E918819
|
entity |
| Predicate | hasAntennaClass |
P13776
|
FINISHED |
| Object | large aperture radio telescope |
—
|
LITERAL 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: large aperture radio telescope | Statement: [RT-70, hasAntennaClass, large aperture radio telescope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAntennaClass Context triple: [RT-70, hasAntennaClass, large aperture radio telescope]
-
A.
hasExternalAntenna
Indicates that an entity is equipped with or connected to an antenna located outside its main body or enclosure.
-
B.
antennaType
chosen
Indicates the specific kind or category of antenna associated with an entity or connection.
-
C.
hasAntennaSpire
Indicates that one entity (typically a structure or building) is equipped with or features an antenna spire.
-
D.
numberOfAntennas
Indicates the quantity of antennas that an entity possesses or is associated with.
-
E.
antennaeSensitivity
Indicates the degree to which an entity’s antennae can detect or respond to external stimuli.
- F. None of above.
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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd5d48855c8190bd93070b6a00d8b5 |
completed | May 8, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69fd5c9aabb88190912800d90184a89d |
completed | May 8, 2026, 3:46 a.m. |
Created at: May 3, 2026, 4:14 p.m.