Triple
T12530546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa |
E299550
|
entity |
| Predicate | relationshipStatusAtBeginning |
P104581
|
FINISHED |
| Object | in a romantic relationship with Matthew |
—
|
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: in a romantic relationship with Matthew | Statement: [Lisa, relationshipStatusAtBeginning, in a romantic relationship with Matthew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusAtBeginning Context triple: [Lisa, relationshipStatusAtBeginning, in a romantic relationship with Matthew]
-
A.
romanticRelationshipStatus
Indicates the nature or state of a romantic relationship between entities, such as whether they are dating, committed, separated, or otherwise romantically involved.
-
B.
relationshipStatusDuringFilm
Indicates the type or state of a relationship between entities specifically during the time period in which a film takes place or is produced.
-
C.
companionshipStatus
Indicates the current state or condition of a relationship of companionship between two or more entities.
-
D.
spouseStatusAtMarriage
Indicates the marital status each partner held at the time their marriage to one another was formed.
-
E.
relationshipStatusInStory
chosen
Indicates the type or state of the relationship between entities as it exists within the context of a specific story or narrative.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.