Triple
T31131427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jose Rodriguez (Fifty Shades Darker) |
E793516
|
entity |
| Predicate | conflictTypeWith Christian Grey |
P1397
|
FINISHED |
| Object | romantic rivalry |
—
|
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 rivalry | Statement: [Jose Rodriguez (Fifty Shades Darker), conflictTypeWith Christian Grey, romantic rivalry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictTypeWith Christian Grey Context triple: [Jose Rodriguez (Fifty Shades Darker), conflictTypeWith Christian Grey, romantic rivalry]
-
A.
conflictType
chosen
Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
-
B.
conflictRole
Indicates that an entity plays a specific role or position within a conflict or dispute between parties.
-
C.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
D.
conflictSpecific
Indicates a specific, concrete instance or type of conflict that exists between the related entities.
-
E.
combinesConfessionsOf
Indicates that one entity merges or brings together the confessions associated with another entity into a single combined form.
- 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_69f224d1701c819094f429798290e361 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6c1bb5f248190834161b5a6ba1ece |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 29, 2026, 9:05 p.m.