Triple
T31839336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Dysart |
E812758
|
entity |
| Predicate | relationshipToAlanStrang |
P207533
|
FINISHED |
| Object | psychiatrist |
—
|
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: psychiatrist | Statement: [Martin Dysart, relationshipToAlanStrang, psychiatrist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAlanStrang Context triple: [Martin Dysart, relationshipToAlanStrang, psychiatrist]
-
A.
relationshipWithAlanHarper
Indicates that one entity has a specified type of personal or social relationship with Alan Harper.
-
B.
relationshipToAlanBennett
Indicates the specific type of personal or professional relationship an entity has with Alan Bennett.
-
C.
relationshipToAlice
Indicates the specific type of relationship or connection that an entity has with Alice.
-
D.
relationshipToAllison
Indicates the specific type of personal, familial, or social relationship that an entity has with Allison.
-
E.
relationshipTypeWith Alonzo Harris
Indicates the specific nature or category of the relationship that an entity has with Alonzo Harris.
- 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_69f348ea7ffc8190a2ab43d80277cf59 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 30, 2026, 11:49 p.m.