Triple
T32874976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master Po |
E840899
|
entity |
| Predicate | relationshipWithKwaiChangCaine |
P202575
|
FINISHED |
| Object | father figure |
—
|
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: father figure | Statement: [Master Po, relationshipWithKwaiChangCaine, father figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithKwaiChangCaine Context triple: [Master Po, relationshipWithKwaiChangCaine, father figure]
-
A.
relationshipToCandide
Indicates the specific type of relationship or connection an entity has to the entity named Candide.
-
B.
relationshipStatusWithKarenCartwright
Indicates the nature or current state of the relationship that an entity has with Karen Cartwright.
-
C.
relationshipToKenny
Indicates the specific familial, social, or interpersonal connection that one entity has to Kenny.
-
D.
hasFictionalRelationshipWith
chosen
Indicates that there exists a fictional or imagined relationship between two entities, such as characters in a story or hypothetical scenarios.
-
E.
relationshipToJoannaKramer
Indicates the specific familial, social, or interpersonal connection that one entity has to Joanna Kramer.
- 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_69f349436ee88190b72ee12d0f3f508e |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:18 a.m.