Triple
T15530522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurent |
E370200
|
entity |
| Predicate | relationshipToMadame Raquin |
P116014
|
FINISHED |
| Object | son-in-law by marriage context |
—
|
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: son-in-law by marriage context | Statement: [Laurent, relationshipToMadame Raquin, son-in-law by marriage context]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMadame Raquin Context triple: [Laurent, relationshipToMadame Raquin, son-in-law by marriage context]
-
A.
relationshipToThérèse Raquin
chosen
Indicates the specific type of relationship or connection an entity has to Thérèse Raquin.
-
B.
relationshipToCamille Raquin
Indicates the specific interpersonal or familial relationship that one entity has to Camille Raquin.
-
C.
relationshipToGoriot
Indicates the type or nature of a person's relationship to Goriot.
-
D.
relationshipToMontresor
Indicates the specific personal or social connection an entity has to Montresor.
-
E.
relationshipToEdmondDantès
Indicates the specific type of personal or social relationship an entity has with Edmond Dantès.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0414773548190b3311515f9d957dd |
completed | April 16, 2026, 1:54 a.m. |
| PD | Predicate disambiguation | batch_69ded28ab0588190a47a9090d1238707 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 4:05 a.m.