Triple
T25689366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joyce Chalfen |
E644156
|
entity |
| Predicate | relationshipToMarcusChalfen |
P192475
|
FINISHED |
| Object | 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: wife | Statement: [Joyce Chalfen, relationshipToMarcusChalfen, wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMarcusChalfen Context triple: [Joyce Chalfen, relationshipToMarcusChalfen, wife]
-
A.
relationshipToMargoChanning
Indicates the nature or type of relationship an entity has with Margo Channing.
-
B.
relationshipToCrassus
Indicates a relationship or association that one entity has with Crassus, specifying how it is connected or related to him.
-
C.
relationshipToGracchus
Indicates the specific familial, social, or political relationship that one entity has to Gracchus.
-
D.
relationshipToMakarDevushkin
Indicates the nature or type of relationship an entity has with Makar Devushkin.
-
E.
relationshipTypeWithMarcus Brewer
Indicates the specific nature or category of relationship that an entity has with Marcus Brewer.
- 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_69e77e8046888190b07ffa58c7e2c37a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69fd0d0aebac8190868a7714ddb4f1fd |
completed | May 7, 2026, 10:07 p.m. |
Created at: April 21, 2026, 8:14 p.m.