Triple
T34821088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annie Bates |
E1003775
|
entity |
| Predicate | relationshipToWalterBates |
P205567
|
FINISHED |
| Object | emotionally estranged wife |
—
|
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: emotionally estranged wife | Statement: [Annie Bates, relationshipToWalterBates, emotionally estranged wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToWalterBates Context triple: [Annie Bates, relationshipToWalterBates, emotionally estranged wife]
-
A.
relationshipToWalterBurns
Indicates the specific nature of the relationship an entity has with Walter Burns, such as familial, professional, or social connection.
-
B.
relationshipToWalterNeff
Indicates that one entity has a specified personal or relational connection to Walter Neff.
-
C.
relationshipToBarnabasCollins
Indicates the type or nature of a subject’s personal or familial connection to Barnabas Collins.
-
D.
relationshipToWinston
Indicates the specific type of personal, social, or familial connection that one entity has with Winston.
-
E.
relationshipToWilbur
Indicates a specified type of relationship or connection that an entity has to Wilbur.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 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_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4 p.m.