Triple
T38367834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trucks in Place |
E892497
|
entity |
| Predicate | languageOfRelatedWork |
P203823
|
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: [Trucks in Place, languageOfRelatedWork, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfRelatedWork Context triple: [Trucks in Place, languageOfRelatedWork, English]
-
A.
languageOfParentWork
Indicates that the specified language is the language in which the parent (original or containing) work is expressed.
-
B.
languageOfTranslatedWorks
Indicates the language into which works have been translated.
-
C.
languageOfUnderlyingWork
Indicates the language in which the original or underlying work (from which a derived or related work stems) is expressed.
-
D.
originalLanguageOfWholeWork
Indicates that a given language is the primary or original language in which an entire work (such as a book, film, or other complete creation) was first produced or expressed.
-
E.
publicationLanguageOfSourceWork
Indicates the language in which the original source work was published.
- 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_69f76e47cb4c8190bdd92cd1db59c0c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0212b3462c8190ba3587852cb10655 |
completed | May 11, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_6a020f3138a48190ac630e810939e881 |
completed | May 11, 2026, 5:17 p.m. |
| PDg | Predicate description generation | batch_6a0212b0f9b081908917bec8e61c9d2e |
completed | May 11, 2026, 5:32 p.m. |
Created at: May 3, 2026, 4:31 p.m.