Triple
T9399537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Assange |
E226431
|
entity |
| Predicate | relationshipToStellaAssange |
P86783
|
FINISHED |
| Object | step-son |
—
|
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: step-son | Statement: [Daniel Assange, relationshipToStellaAssange, step-son]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToStellaAssange Context triple: [Daniel Assange, relationshipToStellaAssange, step-son]
-
A.
relationshipStatusWithDrEvil
Indicates the type or state of a person's relationship with Dr. Evil.
-
B.
relationshipToTony
chosen
Indicates the specific type of relationship or connection that an entity has with Tony.
-
C.
relationshipToHannah
Indicates the specific type of relationship or connection that an entity has to Hannah.
-
D.
hasPoliticalRelationshipWith
Indicates a political connection or association between two entities, such as alliances, rivalries, collaborations, or other forms of political interaction.
-
E.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
- 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_69ca843170f88190800a8ab2b5fc568e |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5156b9588190bafb6b1c3ee3c0ed |
completed | April 1, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69cca545b2448190a4297312e39c21ac |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:46 p.m.