Triple
T13392149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cornelia Srebnick |
E319600
|
entity |
| Predicate | relationshipTypeWithJoshSrebnick |
P109742
|
FINISHED |
| Object | married couple experiencing tension |
—
|
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: married couple experiencing tension | Statement: [Cornelia Srebnick, relationshipTypeWithJoshSrebnick, married couple experiencing tension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithJoshSrebnick Context triple: [Cornelia Srebnick, relationshipTypeWithJoshSrebnick, married couple experiencing tension]
-
A.
relationshipTypeWithJakeBarnes
Indicates the specific nature or category of relationship that an entity has with Jake Barnes.
-
B.
relationshipTypeWithRobertCohn
Indicates the specific nature or category of relationship that an entity has with Robert Cohn.
-
C.
relationshipToQuentinJacobsen
Indicates the specific type of relationship or connection an entity has to Quentin Jacobsen.
-
D.
relationshipTypeWith Francesca Johnson
Indicates the specific nature or category of the relationship that an entity has with Francesca Johnson.
-
E.
relationshipToJoeBuck
Indicates the specific familial, social, or professional relationship that one entity has to the person Joe Buck.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dba0d74e5881909828854bba7d9a87 |
completed | April 12, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03189908190a784a2755f8d81e1 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:34 p.m.