Triple
T8503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | superheterodyne receiver |
E169
|
entity |
| Predicate | isUsedIn |
P98
|
FINISHED |
| Object | AM broadcast receivers |
—
|
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: AM broadcast receivers | Statement: [superheterodyne receiver, isUsedIn, AM broadcast receivers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUsedIn Context triple: [superheterodyne receiver, isUsedIn, AM broadcast receivers]
-
A.
usedFor
chosen
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
B.
hasPart
Indicates that one entity is a component, segment, or constituent part of another entity.
-
C.
describedIn
Indicates that information about an entity is contained or documented within a specified source, such as a text, document, or media.
-
D.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
E.
usedInInternationalTrade
Indicates that something participates as a good, service, or instrument in commercial exchanges between different countries.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2407916ac8190b76d2e6690efaef3 |
completed | Feb. 28, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69a23fe3a87881909ab95bb3a0b474ec |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.