Triple
T13128373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stella Kowalski |
E311901
|
entity |
| Predicate | relationshipToBlanche |
P107614
|
FINISHED |
| Object | younger sister |
—
|
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: younger sister | Statement: [Stella Kowalski, relationshipToBlanche, younger sister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToBlanche Context triple: [Stella Kowalski, relationshipToBlanche, younger sister]
-
A.
relationshipToBlancheDuBois
chosen
Indicates the specific familial, social, or interpersonal connection an entity has with Blanche DuBois.
-
B.
relationshipToMissWatson
Indicates the type or nature of a person's relational connection to Miss Watson (e.g., familial, social, or other defined relationship).
-
C.
relationshipToBenjy
Indicates the specific type of relationship or connection an entity has to Benjy.
-
D.
relationshipWithBlondie
Indicates that there exists some form of relationship or connection between an entity and Blondie.
-
E.
relationshipToMadameMerle
Indicates the specific nature or type of relationship an entity has with Madame Merle.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9819aac388190b59bf43cc6a49d0c |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:07 p.m.