Triple
T22080164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avonlea |
E545627
|
entity |
| Predicate | firstPublicationYearOfFirstAppearance |
P78407
|
FINISHED |
| Object | 1908 |
—
|
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: 1908 | Statement: [Avonlea, firstPublicationYearOfFirstAppearance, 1908]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPublicationYearOfFirstAppearance Context triple: [Avonlea, firstPublicationYearOfFirstAppearance, 1908]
-
A.
firstPublicationYearOfAppearance
chosen
Indicates the year in which an entity (such as a work or character) first appeared in a published form.
-
B.
yearOfFirstApparition
Indicates the calendar year in which the entity first appeared or was introduced.
-
C.
airDateOfFirstAppearance
Indicates the calendar date on which an entity (such as a character, show, or episode) was first broadcast or made publicly available.
-
D.
firstAppearancePublisher
Indicates the publisher responsible for releasing an entity’s first appearance.
-
E.
firstAppearanceApprox
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
- 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b56d5c8190aa825fe02e3ad917 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e6f64a6a70819089d1a6c3a2384861 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:28 p.m.