Triple
T28561704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine Linton |
E722562
|
entity |
| Predicate | forcedMarriageTo |
P122588
|
FINISHED |
| Object | Linton Heathcliff |
—
|
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: Linton Heathcliff | Statement: [Catherine Linton, forcedMarriageTo, Linton Heathcliff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: forcedMarriageTo Context triple: [Catherine Linton, forcedMarriageTo, Linton Heathcliff]
-
A.
forcedMarriage
chosen
Indicates that one entity compels another into a marital union without their free and informed consent.
-
B.
attemptedMarriage
Indicates that one entity tried or intended to enter into a marital relationship with another entity, regardless of whether the marriage was completed or legally recognized.
-
C.
marriesFor
Indicates that one entity enters into marriage with another entity specifically for a particular reason, motive, or benefit.
-
D.
failsToMarry
Indicates that an expected or attempted marriage between entities does not successfully occur.
-
E.
marriageResolvedBy
Indicates that a marital relationship between two parties has been formally concluded or dissolved through a specific resolving action or process (e.g., divorce, annulment).
- 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_69f01a5f69d08190ad5c0d2167078dec |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f650542a1c8190b6f0e66be3bba62c |
completed | May 2, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 4:05 a.m.