Triple
T14779793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camille Raquin |
E347359
|
entity |
| Predicate | deathCausesPlot |
P116066
|
FINISHED |
| Object | drives the plot of Thérèse Raquin |
—
|
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: drives the plot of Thérèse Raquin | Statement: [Camille Raquin, deathCausesPlot, drives the plot of Thérèse Raquin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathCausesPlot Context triple: [Camille Raquin, deathCausesPlot, drives the plot of Thérèse Raquin]
-
A.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
B.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
-
C.
deathCauseUncertainty
Indicates that there is ambiguity, doubt, or lack of definitive information about the cause of death in the relationship being described.
-
D.
deathTollRanking
Indicates the relative position of an event or entity when ordered by the number of deaths it caused, typically from highest to lowest.
-
E.
reasonForDemise
Indicates the cause, circumstance, or factor that led to an entity’s death or termination.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9c7cac8190ba900df95e42e318 |
completed | April 14, 2026, 11:15 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de90c5e3a08190868680b081308c1d |
completed | April 14, 2026, 7:08 p.m. |
Created at: April 10, 2026, 1:31 a.m.