Triple
T25225710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Hobbes |
E632080
|
entity |
| Predicate | relationshipTypeWith Kathryn Janeway |
P10690
|
FINISHED |
| Object | romantic partner |
—
|
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: romantic partner | Statement: [Mark Hobbes, relationshipTypeWith Kathryn Janeway, romantic partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Kathryn Janeway Context triple: [Mark Hobbes, relationshipTypeWith Kathryn Janeway, romantic partner]
-
A.
relationshipStatusWith Kathryn Janeway
Indicates the type or state of the relationship that an entity has with Kathryn Janeway.
-
B.
relationshipTypeWithKatnissEverdeen
Indicates the type or nature of the relationship an entity has with Katniss Everdeen.
-
C.
relationshipTypeWithKaidanAlenko
Indicates the specific nature or category of the relationship an entity has with Kaidan Alenko.
-
D.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
E.
hasRelationshipTypeWith Alexandra Bergson
Indicates that there exists a specific type or category of relationship between an entity and Alexandra Bergson.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 21, 2026, 1:03 p.m.