Triple
T18474771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Józef Teodor Konrad Korzeniowski |
E451400
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Chance
"Chance" is a novel by Joseph Conrad that explores themes of fate, morality, and social convention through the troubled life of a young woman entangled in complex relationships.
|
E1326659
|
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: Chance | Statement: [Józef Teodor Konrad Korzeniowski, notableWork, Chance]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chance Context triple: [Józef Teodor Konrad Korzeniowski, notableWork, Chance]
-
A.
Chance
Chance is a masculine given name often associated with notions of luck, opportunity, and fortune.
-
B.
Chance
"Chance" is a film directed by American filmmaker Jake Schreier, known for his character-driven storytelling and visually polished style.
-
C.
Luck
Luck is a common English surname borne by various notable individuals in sports, entertainment, and other fields.
-
D.
Luck
Luck is an American television drama series centered on the world of horse racing and gambling, known for its ensemble cast and gritty portrayal of the racing industry.
-
E.
Luck
"Luck" is a 2022 animated fantasy comedy film about a perpetually unlucky girl who discovers a secret world of good and bad luck.
- 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: Chance Triple: [Józef Teodor Konrad Korzeniowski, notableWork, Chance]
Generated description
"Chance" is a novel by Joseph Conrad that explores themes of fate, morality, and social convention through the troubled life of a young woman entangled in complex relationships.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chance Target entity description: "Chance" is a novel by Joseph Conrad that explores themes of fate, morality, and social convention through the troubled life of a young woman entangled in complex relationships.
-
A.
Chance
Chance is a masculine given name often associated with notions of luck, opportunity, and fortune.
-
B.
Chance
"Chance" is a film directed by American filmmaker Jake Schreier, known for his character-driven storytelling and visually polished style.
-
C.
Luck
Luck is a common English surname borne by various notable individuals in sports, entertainment, and other fields.
-
D.
Luck
"Luck" is a 2022 animated fantasy comedy film about a perpetually unlucky girl who discovers a secret world of good and bad luck.
-
E.
Luck
Luck is an American television drama series centered on the world of horse racing and gambling, known for its ensemble cast and gritty portrayal of the racing industry.
- 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53062387481909d4503fc963f9913 |
completed | April 19, 2026, 7:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a043f2ae2888190ae12fee12cf419ff |
completed | May 13, 2026, 9:06 a.m. |
| NEDg | Description generation | batch_6a043fd646b88190b0d232e740ae22ba |
completed | May 13, 2026, 9:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04403951608190bc24c914175f18bc |
completed | May 13, 2026, 9:11 a.m. |
Created at: April 10, 2026, 11:34 a.m.