Triple
T20881996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telefon |
E514173
|
entity |
| Predicate | hasMetacriticType |
P54693
|
FINISHED |
| Object | movie |
—
|
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: movie | Statement: [Telefon, hasMetacriticType, movie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetacriticType Context triple: [Telefon, hasMetacriticType, movie]
-
A.
hasMetacriticId
Indicates that an entity is associated with a specific identifier used by Metacritic to reference it in their database.
-
B.
hasMetacriticPage
Indicates that an entity has a dedicated page or entry on the Metacritic review aggregation website.
-
C.
metacriticCategory
chosen
Indicates that one entity is classified under a specific Metacritic-defined category (such as a media type, genre, or section) in the Metacritic system.
-
D.
hasMetascore
Indicates that an entity is associated with a Metascore rating, typically representing an aggregated critical review score.
-
E.
metacriticReception
Indicates the critical reception or review score an entity received on Metacritic.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c67a33548190b0f5ba58b001d387 |
completed | April 21, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:46 p.m.