Triple
T2246394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Count László de Almásy |
E49513
|
entity |
| Predicate | romanticRelationshipType |
P9994
|
FINISHED |
| Object | adulterous affair |
—
|
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: adulterous affair | Statement: [Count László de Almásy, romanticRelationshipType, adulterous affair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticRelationshipType Context triple: [Count László de Almásy, romanticRelationshipType, adulterous affair]
-
A.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
fictionalRelationship
Indicates a relationship that exists only within a fictional or imagined context between entities.
-
C.
spouseOrLover
chosen
Indicates a romantic partnership between two entities, whether formalized as a spouse or existing as a lover.
-
D.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
-
E.
companionshipStatus
Indicates the current state or condition of a relationship of companionship between two or more 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0ec46b08190ae12de8b255eb71d |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.