Triple
T13192971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucien de Rubempré |
E314038
|
entity |
| Predicate | romanticRelationship |
P9994
|
FINISHED |
| Object |
Coralie
Coralie is a beautiful young actress in Honoré de Balzac’s novel "Lost Illusions," known for her tragic love affair with the ambitious poet Lucien de Rubempré.
|
E1027381
|
NE FINISHED |
How this triple was built (4 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: Coralie | Statement: [Lucien de Rubempré, romanticRelationship, Coralie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coralie Context triple: [Lucien de Rubempré, romanticRelationship, Coralie]
-
A.
Clemie
Clemie is a given name, typically used as a diminutive or variant of the name Clem.
-
B.
Cécile
Cécile is the sensitive and central protagonist of the French film "Cible émouvante," around whom the story’s emotional and narrative developments revolve.
-
C.
Laureline
Laureline is a courageous and quick-witted space-time agent who partners with Valerian in the sci-fi universe of "Valerian and the City of a Thousand Planets."
-
D.
Lila
Lila is the daughter of French actress Virginie Ledoyen.
-
E.
Lila
Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Coralie Triple: [Lucien de Rubempré, romanticRelationship, Coralie]
Generated description
Coralie is a beautiful young actress in Honoré de Balzac’s novel "Lost Illusions," known for her tragic love affair with the ambitious poet Lucien de Rubempré.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Coralie Target entity description: Coralie is a beautiful young actress in Honoré de Balzac’s novel "Lost Illusions," known for her tragic love affair with the ambitious poet Lucien de Rubempré.
-
A.
Clemie
Clemie is a given name, typically used as a diminutive or variant of the name Clem.
-
B.
Cécile
Cécile is the sensitive and central protagonist of the French film "Cible émouvante," around whom the story’s emotional and narrative developments revolve.
-
C.
Laureline
Laureline is a courageous and quick-witted space-time agent who partners with Valerian in the sci-fi universe of "Valerian and the City of a Thousand Planets."
-
D.
Lila
Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
-
E.
Lila
Lila is a novel by Marilynne Robinson that continues her acclaimed Gilead series, exploring themes of grace, poverty, and belonging through the life of its enigmatic title character.
- F. None of above. chosen
Provenance (5 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c6158e4819082c8ad75b4dfdd90 |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5fef9e48190961d66ebcc1df11f |
completed | May 3, 2026, 7:15 a.m. |
| NEDg | Description generation | batch_69f6f80b420c8190b5028be4fa99fb59 |
completed | May 3, 2026, 7:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6f89072a88190b3182f581b1b6762 |
completed | May 3, 2026, 7:26 a.m. |
Created at: April 9, 2026, 9:16 p.m.