Triple
T26942876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Walker |
E678564
|
entity |
| Predicate | mcuMedium |
P166
|
FINISHED |
| Object | television series |
—
|
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: television series | Statement: [John Walker, mcuMedium, television series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mcuMedium Context triple: [John Walker, mcuMedium, television series]
-
A.
mediumAdaptedTo
Indicates that a medium (such as a format, channel, or platform) has been specifically adjusted or tailored to suit a particular use, context, or target.
-
B.
medium
chosen
Indicates that an entity serves as the means, channel, or intermediary through which an action, communication, or effect is carried out between other entities.
-
C.
mediumCoreCount
Indicates that an entity has a moderate or intermediate number of processing cores relative to a defined scale or range.
-
D.
mediumRecognized
Indicates that a medium (such as a channel, format, or communication method) has been identified and acknowledged as valid or known within a given context.
-
E.
mediumCategory
Indicates the classification of an item or content according to the type or form of medium it belongs to (e.g., print, digital, audio, video).
- 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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f620822d6081908e38814f5a1c0931 |
completed | May 2, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 6:19 a.m.