Triple
T22103634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fauchelevent |
E546230
|
entity |
| Predicate | relationshipToJeanValjean |
P146990
|
FINISHED |
| Object | beneficiary of rescue |
—
|
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: beneficiary of rescue | Statement: [Fauchelevent, relationshipToJeanValjean, beneficiary of rescue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToJeanValjean Context triple: [Fauchelevent, relationshipToJeanValjean, beneficiary of rescue]
-
A.
relationshipToMonsieurJourdain
Indicates the type or nature of a person’s relationship to Monsieur Jourdain.
-
B.
relationshipToEdmondDantès
Indicates the specific type of personal or social relationship an entity has with Edmond Dantès.
-
C.
relationshipToGoriot
Indicates the type or nature of a person's relationship to Goriot.
-
D.
relationshipToBobinot
Indicates the nature or type of relationship that one entity has with Bobinot.
-
E.
relationshipToBaudelaires
Indicates the type of personal or familial connection an entity has to the Baudelaires.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129175a7881909549883f23c53dca |
completed | April 28, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69e71b20ec50819096ac196c798f8e3c |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:30 p.m.