Triple
T37971249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | People v. Balfour |
E947290
|
entity |
| Predicate | relationshipToVictimJuliaHudson |
P138296
|
FINISHED |
| Object | estranged husband |
—
|
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: estranged husband | Statement: [People v. Balfour, relationshipToVictimJuliaHudson, estranged husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToVictimJuliaHudson Context triple: [People v. Balfour, relationshipToVictimJuliaHudson, estranged husband]
-
A.
allegedVictimOf
Indicates that one entity is claimed or reported to have been harmed, wronged, or victimized by another entity, without asserting that the claim is proven.
-
B.
relationshipToJulia
chosen
Indicates the specific type of personal or social relationship that an entity has with Julia.
-
C.
relationshipToJulie
Indicates a specified type of relationship or connection that an entity has to Julie.
-
D.
hasRelationshipToPerpetrator
Indicates that an entity has a specified type of relationship or connection to the perpetrator of an act or event.
-
E.
relationshipToLavinia
Indicates the nature or type of relationship an entity has with Lavinia.
- 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_69f76ef7db908190bba6086673a32300 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.