Triple
T33224788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archbishop Laud, 1573–1645 |
E850523
|
entity |
| Predicate | subjectBirthYearInTitle |
P33319
|
FINISHED |
| Object | 1573 |
—
|
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: 1573 | Statement: [Archbishop Laud, 1573–1645, subjectBirthYearInTitle, 1573]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectBirthYearInTitle Context triple: [Archbishop Laud, 1573–1645, subjectBirthYearInTitle, 1573]
-
A.
hasYearInTitle
chosen
Indicates that the title of an entity explicitly contains a year value as part of its text.
-
B.
EuroTitleYear
Indicates the year in which an entity received or held a specific European title or championship.
-
C.
titleYear
Indicates the specific year associated with the release, publication, or official designation of a given title.
-
D.
yearTitleCreated
Indicates the year in which the referenced title (such as a work, document, or creative piece) was originally created.
-
E.
revisedTitleYear
Indicates that an entity’s title was revised or updated in the specified year.
- 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_69f3496083dc8190b229bb6932dc548b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: May 1, 2026, 1:30 a.m.