Triple
T37774093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame d'Arblay |
E941636
|
entity |
| Predicate | firstPublishedWorkPublicationYear |
P145347
|
FINISHED |
| Object | 1778 |
—
|
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: 1778 | Statement: [Madame d'Arblay, firstPublishedWorkPublicationYear, 1778]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPublishedWorkPublicationYear Context triple: [Madame d'Arblay, firstPublishedWorkPublicationYear, 1778]
-
A.
firstPublishedInWorkYear
Indicates the year in which a work was first published.
-
B.
firstPublishedWork
chosen
Indicates that one work is the earliest piece created or released by a particular creator or entity.
-
C.
firstChapterPublicationYear
Indicates the year in which the first chapter of a work was originally published.
-
D.
firstCompletePublicationYear
Indicates the calendar year in which an entity’s first complete publication was released.
-
E.
firstAssociatedPublicationYear
Indicates the calendar year in which an entity’s earliest associated publication was first released or made publicly available.
- 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_69f76ee4431881908f87e8892a9f39f3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.