Triple
T22980639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Remember It Well |
E571451
|
entity |
| Predicate | depictsRelationshipType |
P23406
|
FINISHED |
| Object | former lovers |
—
|
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: former lovers | Statement: [I Remember It Well, depictsRelationshipType, former lovers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsRelationshipType Context triple: [I Remember It Well, depictsRelationshipType, former lovers]
-
A.
portraysRelationship
chosen
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
-
B.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
showsRelationshipWith
Indicates that one entity visually or explicitly presents or demonstrates its connection or association with another entity.
-
D.
definesRelationshipAs
Indicates that one entity explicitly specifies or establishes the type or nature of the relationship that holds between two or more entities.
-
E.
plotRelation
Indicates a narrative connection between two story elements, such as events, characters, or subplots, showing how one influences or relates to the other within the overall plot.
- 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1829589548190863619aebcae026c |
completed | April 29, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:49 p.m.