Triple
T28869630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melinda Welles |
E729105
|
entity |
| Predicate | romanticPlotInvolves |
P154818
|
FINISHED |
| Object | relationships across time |
—
|
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: relationships across time | Statement: [Melinda Welles, romanticPlotInvolves, relationships across time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticPlotInvolves Context triple: [Melinda Welles, romanticPlotInvolves, relationships across time]
-
A.
romanticPlotFunction
Indicates a narrative relationship where characters are involved in or contribute to a romantic storyline or romantic development within the plot.
-
B.
romanticSubplotCentral
Indicates that a romantic subplot is a primary, driving element of the narrative rather than a minor or peripheral thread.
-
C.
hasRomanticPlotline
chosen
Indicates that there is a romantic storyline or relationship development present between the entities.
-
D.
romanticOutcome
Indicates that a romantic relationship or interaction between entities results in a particular outcome, such as success, failure, or change in status.
-
E.
romanticArc
Indicates a developing or ongoing romantic relationship or storyline between the involved 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_69f031a01cbc8190ba87270bb6fe4639 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f66d7765208190b87b1cc6d96a151c |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 6:50 a.m.