Triple
T8667695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subramaniapuram |
E205715
|
entity |
| Predicate | languageSubtitledIn |
P47403
|
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: [Subramaniapuram, languageSubtitledIn, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageSubtitledIn Context triple: [Subramaniapuram, languageSubtitledIn, English]
-
A.
languageDubbedIn
Indicates that the content’s audio has been dubbed into the specified language.
-
B.
languageOfSubtitles
chosen
Indicates the language in which the subtitles for a given media item are provided.
-
C.
hasSubtitles
Indicates that one media item provides subtitle text or tracks that accompany another media item or its audio content.
-
D.
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).
-
E.
languageOfSeries
Indicates the language in which a series is primarily produced, presented, or officially released.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a34b808190aa9aed9cdb2900e6 |
completed | March 31, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:31 p.m.