Triple
T37605838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Louis Stevenson Trail (GR 70) |
E935648
|
entity |
| Predicate | languageOfOriginalBook |
P74798
|
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: [Robert Louis Stevenson Trail (GR 70), languageOfOriginalBook, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfOriginalBook Context triple: [Robert Louis Stevenson Trail (GR 70), languageOfOriginalBook, English]
-
A.
originalLanguageOfWholeWork
chosen
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.
-
B.
languageOfBooks
Indicates the language in which the referenced books are written or published.
-
C.
languageOfAuthor
Indicates the language in which an author writes or has written their works.
-
D.
languageOfOriginalDescription
Indicates that something is expressed or documented in its initial or source language version.
-
E.
languageOfParentWork
Indicates that the specified language is the language in which the parent (original or containing) work is expressed.
- 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_69f76ed0a85481909254a8a89090c826 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a01a0b63d148190b10206509c0a0a5b |
completed | May 11, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_6a01a0245d4c8190a3c3fbbe83f0389d |
completed | May 11, 2026, 9:23 a.m. |
Created at: May 3, 2026, 4:18 p.m.