Triple
T20398034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lassie |
E500258
|
entity |
| Predicate | televisionSeriesLanguage |
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: [Lassie, televisionSeriesLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: televisionSeriesLanguage Context triple: [Lassie, televisionSeriesLanguage, English]
-
A.
languageOfSeries
chosen
Indicates the language in which a series is primarily produced, presented, or officially released.
-
B.
hasLanguageOfShows
Indicates that an entity (such as a channel, platform, or schedule) is associated with the language in which its shows are presented.
-
C.
languageSpokenOnScreen
Indicates that a particular language is used in spoken dialogue or audible communication within an on-screen work (such as a film, show, or video).
-
D.
languageOfPrimaryBroadcasts
Indicates the language in which an entity’s primary broadcasts are delivered.
-
E.
languageDubbedIn
Indicates that the content’s audio has been dubbed into the specified language.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6798c2b28819092fab93f01218cde |
completed | April 20, 2026, 7:07 p.m. |
| PD | Predicate disambiguation | batch_69e5765d7cb48190adec18d6d1e3d263 |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:29 a.m.