Triple
T29455016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funkgerät 212 |
E747074
|
entity |
| Predicate | radarFamily |
P167204
|
FINISHED |
| Object | Lichtenstein series of AI radars |
—
|
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: Lichtenstein series of AI radars | Statement: [Funkgerät 212, radarFamily, Lichtenstein series of AI radars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: radarFamily Context triple: [Funkgerät 212, radarFamily, Lichtenstein series of AI radars]
-
A.
radarType
Indicates the specific category or classification of radar associated with an entity.
-
B.
radarFunction
Indicates that one entity serves as the functional role, purpose, or operational capability of a radar system in relation to another entity.
-
C.
radarInterface
Indicates that one entity serves as or provides a radar-based interface or interaction layer for another entity.
-
D.
radarEquipment
Indicates that one entity is radar equipment used for detecting, tracking, or measuring objects relative to another entity.
-
E.
associatedRadar
Indicates that one entity is linked or connected to a specific radar system or radar-related resource.
- F. None of above. chosen
Provenance (4 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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66b6c26a481908018e663aee7b269 |
completed | May 2, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f663ff176c8190aaadb475f75daee4 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 28, 2026, 3:36 p.m.