Triple
T14646561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JH 1580 |
E343865
|
entity |
| Predicate | workLanguageOfTitle |
P115202
|
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: [JH 1580, workLanguageOfTitle, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLanguageOfTitle Context triple: [JH 1580, workLanguageOfTitle, English]
-
A.
areSpokenIn
Indicates that a particular language is used as a spoken means of communication within a specified region, community, or context.
-
B.
filmedInLanguage
Indicates that a film or video work was originally recorded using a particular spoken or signed language.
-
C.
primaryFilmingLanguage
Indicates the main language in which a film or audiovisual work was originally filmed or recorded.
-
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.
officialLanguageOfTitle
Indicates that a specified language is the officially designated language associated with a particular title or position.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ebe8048190a2935d00c9cfd8be |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:26 a.m.