Triple
T35452670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zack Brown |
E1024678
|
entity |
| Predicate | relationshipTypeWithMiriLinky |
P10690
|
FINISHED |
| Object | friends-to-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: friends-to-lovers | Statement: [Zack Brown, relationshipTypeWithMiriLinky, friends-to-lovers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithMiriLinky Context triple: [Zack Brown, relationshipTypeWithMiriLinky, friends-to-lovers]
-
A.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
relationshipTarget
Indicates that an entity is the object or recipient toward which a specified relationship is directed.
-
C.
relationshipToUser
Indicates the type of connection or association an entity has with the current user.
-
D.
identityRelation
Indicates that two entities are in fact the very same entity, not merely similar or equivalent.
-
E.
addressesRelationship
Indicates that one entity directs communication, remarks, or attention specifically toward another entity.
- 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_69f76df92f108190817222e520e22268 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:04 p.m.