Triple
T14106192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TF1 |
E339510
|
entity |
| Predicate | terrestrialChannel |
P112830
|
FINISHED |
| Object | Channel 1 (HD) in most of France |
—
|
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: Channel 1 (HD) in most of France | Statement: [TF1, terrestrialChannel, Channel 1 (HD) in most of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrestrialChannel Context triple: [TF1, terrestrialChannel, Channel 1 (HD) in most of France]
-
A.
terrestrialService
Indicates a service or operation that is provided on or relates specifically to land-based (earthbound) environments, as opposed to aerial, maritime, or space-based contexts.
-
B.
terrestrialDiscoveryContext
Indicates the context or circumstances under which something was discovered on Earth or in a land-based environment.
-
C.
hasTerrestrialArea
Indicates that an entity possesses a specified extent of land area on the Earth's surface.
-
D.
typicalChannel
Indicates the usual or most commonly used communication or distribution channel through which an interaction, message, or transaction typically occurs.
-
E.
laterChannelRegion
Indicates that one channel region occurs or is positioned later in sequence or time relative to another channel region.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de600ada808190b92d67dc30f13d15 |
completed | April 14, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:22 p.m.