Triple
T10642211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron de Wolmar |
E250749
|
entity |
| Predicate | relationshipToSaint-Preux |
P95127
|
FINISHED |
| Object | Julie's rival in love |
—
|
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: Julie's rival in love | Statement: [Baron de Wolmar, relationshipToSaint-Preux, Julie's rival in love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToSaint-Preux Context triple: [Baron de Wolmar, relationshipToSaint-Preux, Julie's rival in love]
-
A.
relationshipToPierreBezukhov
Indicates the specific type of personal or social relationship an entity has to Pierre Bezukhov.
-
B.
relationshipWithHumbertHumbert
Indicates that an entity has a specified type of personal, emotional, or social relationship with Humbert Humbert.
-
C.
relationshipToGilbertOsmond
Indicates the specific type of personal or social relationship that an entity has with Gilbert Osmond.
-
D.
relationshipToMadameMerle
Indicates the specific nature or type of relationship an entity has with Madame Merle.
-
E.
relationshipToGustav von Aschenbach
Indicates the specific type of personal, social, or emotional connection an entity has to Gustav von Aschenbach.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfce1ddc8190893fe6f7b047b56b |
completed | April 8, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69d6dd83b114819098e84dc658e82d7e |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df463ea8819091d6683e476b4f21 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:05 p.m.