Triple
T25033991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liza of Lambeth |
E626925
|
entity |
| Predicate | hasLoveAffairPlot |
P154818
|
FINISHED |
| Object | Liza Kemp and Jim Blakeston |
—
|
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: Liza Kemp and Jim Blakeston | Statement: [Liza of Lambeth, hasLoveAffairPlot, Liza Kemp and Jim Blakeston]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoveAffairPlot Context triple: [Liza of Lambeth, hasLoveAffairPlot, Liza Kemp and Jim Blakeston]
-
A.
hasRomanticPlotline
chosen
Indicates that there is a romantic storyline or relationship development present between the entities.
-
B.
hasRomanticSubplot
Indicates that a work includes a secondary storyline centered on a romantic relationship between characters.
-
C.
hasMarriagePlot
Indicates that the work’s narrative centrally involves courtship, romantic relationships, or the progression toward marriage as a key plot element.
-
D.
romanticSubplotCentral
Indicates that a romantic subplot is a primary, driving element of the narrative rather than a minor or peripheral thread.
-
E.
hasRomanticMisadventures
Indicates that an entity experiences a series of problematic, comical, or unsuccessful romantic relationships or encounters.
- 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_69e2ff2a2c088190be513727ee8bfe78 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f638d11c988190af7fd4572b08e038 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f63706b6008190993577193c85ff50 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 18, 2026, 6:07 a.m.