Triple
T4176969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ali Baba |
E86499
|
entity |
| Predicate | firstKnownInPrint |
P3921
|
FINISHED |
| Object | 18th century French translation of One Thousand and One Nights |
—
|
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: 18th century French translation of One Thousand and One Nights | Statement: [Ali Baba, firstKnownInPrint, 18th century French translation of One Thousand and One Nights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstKnownInPrint Context triple: [Ali Baba, firstKnownInPrint, 18th century French translation of One Thousand and One Nights]
-
A.
firstPublicationIn
Indicates the initial venue, medium, or context in which a work was first published.
-
B.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
C.
firstClearlyAttestedIn
chosen
Indicates the earliest known point in time or source where something is clearly documented or evidenced.
-
D.
firstPrintedInPlace
Indicates the place where an item (such as a work or edition) was first printed.
-
E.
firstQuartoPublicationDate
Indicates the calendar date on which the first edition of a work was published in quarto format.
- 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_69aed93de98c8190ad838ce507b77c8a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af07078cb081909f64326b12522410 |
completed | March 9, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69af019155448190b19868583272513f |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:45 p.m.