Triple
T25308749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bag Man |
E634550
|
entity |
| Predicate | podcastLanguage |
P51969
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Bag Man, podcastLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: podcastLanguage Context triple: [Bag Man, podcastLanguage, English]
-
A.
pronunciationLanguage
Indicates the language in which the pronunciation of an entity (such as a word or name) is given.
-
B.
primaryLanguageInSeries
Indicates that a given language is the main or predominant language used throughout a particular series.
-
C.
languageDiscussedIn
Indicates that a particular language is the topic of discussion within a specified context, source, or discourse.
-
D.
languageOfSeries
chosen
Indicates the language in which a series is primarily produced, presented, or officially released.
-
E.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
- 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_69e75a972c6481909bc11710e8d30a6c |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f4939c49a48190b9fdc2555273915e |
completed | May 1, 2026, 11:50 a.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:25 p.m.