Triple
T661051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hell on Wheels |
E11755
|
entity |
| Predicate | originalChannelType |
P2595
|
FINISHED |
| Object | cable television network |
—
|
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: cable television network | Statement: [Hell on Wheels, originalChannelType, cable television network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalChannelType Context triple: [Hell on Wheels, originalChannelType, cable television network]
-
A.
originalChannel
chosen
Indicates the communication channel or medium through which something was first created, sent, or published.
-
B.
originalType
Indicates that one entity represents the initial or source type from which another entity is derived, transformed, or reclassified.
-
C.
sisterChannel
Indicates that one channel is a sibling or counterpart to another channel, typically under the same ownership or network.
-
D.
virtualChannel
Indicates that one entity is linked to another through a non-physical, software-defined communication channel used for transmitting data or signals.
-
E.
originalTrafficType
Indicates the initial category or source classification of traffic before any changes, redirects, or reattributions occur.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d1406ec8190abf546549264c85d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.