Triple
T16138433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica |
E391589
|
entity |
| Predicate | firstMajorLiteraryAppearanceYearApprox |
P85246
|
FINISHED |
| Object | late 16th century |
—
|
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: late 16th century | Statement: [Jessica, firstMajorLiteraryAppearanceYearApprox, late 16th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMajorLiteraryAppearanceYearApprox Context triple: [Jessica, firstMajorLiteraryAppearanceYearApprox, late 16th century]
-
A.
firstPublishedInWorkYear
Indicates the year in which a work was first published.
-
B.
debutWorkReleaseYear
Indicates the calendar year in which an entity’s first published or publicly released work originally came out.
-
C.
firstWellKnownLiteraryVersionYear
chosen
Indicates the year in which the first well-known literary version of something (such as a story, character, or motif) was published or recorded.
-
D.
firstCompletePublicationYear
Indicates the calendar year in which an entity’s first complete publication was released.
-
E.
firstPublicationYearOfAppearance
Indicates the year in which an entity (such as a work or character) first appeared in a published form.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a06e0988190b5cd62d422d058a2 |
completed | April 17, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.