Triple
T20416198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosaline |
E500717
|
entity |
| Predicate | demandsFromBerowne |
P140058
|
FINISHED |
| Object | a year of service and reformation |
—
|
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: a year of service and reformation | Statement: [Rosaline, demandsFromBerowne, a year of service and reformation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demandsFromBerowne Context triple: [Rosaline, demandsFromBerowne, a year of service and reformation]
-
A.
demandsAsBride
Indicates that one entity insists on taking another entity specifically as a bride, typically as a condition or demand.
-
B.
demandsFromConor
Indicates that one entity makes a demand or requirement directed toward Conor.
-
C.
wantsHermiaToMarry
Indicates that one entity desires or intends for Hermia to enter into marriage, typically with a specific person.
-
D.
demands
Indicates that one entity insists that another entity provide something or take a specific action, typically with authority or urgency.
-
E.
asksToMarry
Indicates that one entity proposes marriage to another, requesting that they become spouses.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a4437448190b07b6e6e3de5830f |
completed | April 20, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69e5766df0008190a73c4f613c29678f |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:30 a.m.