Triple
T5907921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Éponine |
E131386
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object | Thénardier |
E545916
|
NE 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: Thénardier | Statement: [Éponine, parent, Thénardier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thénardier Context triple: [Éponine, parent, Thénardier]
-
A.
Thénardiers
chosen
The Thénardiers are a cruel and exploitative innkeeping couple in Victor Hugo's "Les Misérables" who abuse and extort the child left in their care.
-
B.
Madame Defarge
Madame Defarge is a vengeful, knitting revolutionary in Charles Dickens' "A Tale of Two Cities," emblematic of the ruthless spirit of the French Revolution.
-
C.
Fantine
Fantine is a tragic young mother in Victor Hugo's Les Misérables, whose descent into poverty and sacrifice for her child embodies the novel’s social injustice and emotional core.
-
D.
Madame Vauquer
Madame Vauquer is the miserly, aging widow who runs the shabby Parisian boarding house in Balzac’s novel "Le Père Goriot."
-
E.
Danglars
Danglars is a greedy, treacherous banker and one of the chief conspirators against Edmond Dantès in Alexandre Dumas’ novel *The Count of Monte Cristo*.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c008593a44819081a07ae0efe6c574 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03773f4188190a11276b2d5baad08 |
completed | March 22, 2026, 6:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11cbc676c8190bdac874391a608e8 |
completed | March 23, 2026, 10:58 a.m. |
Created at: March 22, 2026, 3:59 p.m.