Triple
T28269969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Holland (betrothed) |
E712818
|
entity |
| Predicate | betrothalType |
P164668
|
FINISHED |
| Object | arranged noble marriage |
—
|
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: arranged noble marriage | Statement: [Henry Holland (betrothed), betrothalType, arranged noble marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: betrothalType Context triple: [Henry Holland (betrothed), betrothalType, arranged noble marriage]
-
A.
betrothalDuration
Indicates the length of time that a betrothal or engagement between two parties lasts or is intended to last.
-
B.
betrothalEnd
Indicates that a previously established engagement or betrothal between two parties has been terminated or dissolved.
-
C.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
D.
betrothalAge
Indicates the age at which a person becomes formally engaged to be married.
-
E.
betrothalYear
Indicates the year in which two entities became formally engaged to be married.
- F. None of above. chosen
Provenance (4 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f64ee0c2788190a94a04ad1902fd5e |
completed | May 2, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69f64caede108190a35cc7cbfead866f |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f64e36c57c8190af09470a8d35512b |
completed | May 2, 2026, 7:19 p.m. |
Created at: April 27, 2026, 11:17 p.m.