Triple
T20223421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosalind and Orlando |
E495315
|
entity |
| Predicate | courtshipMode |
P139291
|
FINISHED |
| Object | witty banter |
—
|
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: witty banter | Statement: [Rosalind and Orlando, courtshipMode, witty banter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtshipMode Context triple: [Rosalind and Orlando, courtshipMode, witty banter]
-
A.
asksToMarry
Indicates that one entity proposes marriage to another, requesting that they become spouses.
-
B.
marriagePattern
Indicates the typical form or structure of a marriage relationship, such as how partners are selected, organized, or related within a social or cultural system.
-
C.
desiredMarriageWith
Indicates that one entity wishes to enter into a marital relationship with another entity.
-
D.
encouragesRomanceBetween
Indicates that one entity promotes, supports, or fosters a romantic relationship between two other entities.
-
E.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fd827708190b798a30f4e7d533f |
completed | April 20, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56702ad04819099c1c08f28d16809 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:39 p.m.