Triple
T35000532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chance Wayne |
E1009661
|
entity |
| Predicate | relationshipTypeWith Princess Kosmonopolis |
P206792
|
FINISHED |
| Object | exploitative partnership |
—
|
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: exploitative partnership | Statement: [Chance Wayne, relationshipTypeWith Princess Kosmonopolis, exploitative partnership]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Princess Kosmonopolis Context triple: [Chance Wayne, relationshipTypeWith Princess Kosmonopolis, exploitative partnership]
-
A.
relationshipToPrincess
Indicates the specific familial, social, or romantic connection that one entity has to a princess.
-
B.
relationshipTypeWithPrinceChar
Indicates the specific kind or nature of relationship an entity has with the prince character.
-
C.
relationshipToPolinaAlexandrovna
Indicates the specific type of personal or social relationship that one entity has with Polina Alexandrovna.
-
D.
hasRelationshipTypeWith Anastasia Steele
Indicates that an entity has a specific type of relationship or relational role with Anastasia Steele.
-
E.
relationshipTypeWithTiamat
Indicates the specific nature or category of relationship an entity has with Tiamat.
- F. None of above. chosen
Provenance (4 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_69f76dcb716881909f75e4fd60ab2284 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:01 p.m.