Triple
T14015984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TNT (French digital terrestrial television) |
E337204
|
entity |
| Predicate | primaryReceptionMethod |
P112473
|
FINISHED |
| Object | rooftop antenna |
—
|
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: rooftop antenna | Statement: [TNT (French digital terrestrial television), primaryReceptionMethod, rooftop antenna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryReceptionMethod Context triple: [TNT (French digital terrestrial television), primaryReceptionMethod, rooftop antenna]
-
A.
primaryIntakeType
Indicates the main or most significant type of intake or input associated with an entity or process.
-
B.
initialReception
Indicates the nature or quality of the first response or reaction something receives when it is introduced or presented.
-
C.
appointmentMethod
Indicates how an appointment is arranged, such as the channel, process, or means used to schedule it.
-
D.
primaryFor
Indicates that one entity serves as the main or principal option, resource, or association for another entity among possible alternatives.
-
E.
primaryIntake
Indicates that one entity serves as the main or first point of intake, reception, or admission for another entity.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2f396b648190927e5718c3bb6511 |
completed | April 14, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69de05a802ac819090604025aae6a4d5 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239524688190a0f2408c239cfcaa |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:19 p.m.