Triple
T26249587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Elton |
E656543
|
entity |
| Predicate | courtshipTarget |
P138576
|
FINISHED |
| Object | Emma Woodhouse |
—
|
NE NERFINISHED |
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: Emma Woodhouse | Statement: [Mr. Elton, courtshipTarget, Emma Woodhouse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtshipTarget Context triple: [Mr. Elton, courtshipTarget, Emma Woodhouse]
-
A.
courtshipMode
Indicates the manner or strategy by which one entity engages in behaviors intended to attract or win the favor of another for a romantic or reproductive relationship.
-
B.
asksToMarry
Indicates that one entity proposes marriage to another, requesting that they become spouses.
-
C.
desiredMarriageWith
chosen
Indicates that one entity wishes to enter into a marital relationship with another entity.
-
D.
loveInterestPortrayedBy
Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
-
E.
loveInterestType
Indicates the specific kind or category of romantic or affectionate relationship that exists between the related entities.
- 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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f60dc94bf881908c91f372e8880a0e |
completed | May 2, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 9:06 p.m.