Triple
T2815659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chance King |
E54277
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Chance
Chance is a masculine given name often associated with notions of luck, opportunity, and fortune.
|
E300778
|
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: [Chance King, givenName, Chance]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chance Context triple: [Chance King, givenName, Chance]
-
A.
Luck
"Luck" is a 2022 animated fantasy comedy film about a perpetually unlucky girl who discovers a secret world of good and bad luck.
-
B.
Chancy
Chancy is a small Swiss municipality located at the western tip of the canton of Geneva, near the border with France.
-
C.
Time and Chance
"Time and Chance" is a notable work by British musician and songwriter Peter Townsend, reflecting his contributions beyond his role in The Who.
-
D.
Random
Random is a Julia standard library module that provides functionality for generating and manipulating random numbers and random processes.
-
E.
Riskin
Riskin is a surname most notably associated with American screenwriter Robert Riskin, renowned for his collaborations with director Frank Capra during Hollywood’s Golden Age.
- 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: [Chance King, givenName, Chance]
Generated description
Chance is a masculine given name often associated with notions of luck, opportunity, and fortune.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chance Target entity description: Chance is a masculine given name often associated with notions of luck, opportunity, and fortune.
-
A.
Luck
"Luck" is a 2022 animated fantasy comedy film about a perpetually unlucky girl who discovers a secret world of good and bad luck.
-
B.
Chancy
Chancy is a small Swiss municipality located at the western tip of the canton of Geneva, near the border with France.
-
C.
Time and Chance
"Time and Chance" is a notable work by British musician and songwriter Peter Townsend, reflecting his contributions beyond his role in The Who.
-
D.
Random
Random is a Julia standard library module that provides functionality for generating and manipulating random numbers and random processes.
-
E.
Riskin
Riskin is a surname most notably associated with American screenwriter Robert Riskin, renowned for his collaborations with director Frank Capra during Hollywood’s Golden Age.
- 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4ed4ac81909f1ec4a3f7869bc1 |
completed | March 7, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afce9f964081909e422aaf1f026dbb |
completed | March 10, 2026, 7:56 a.m. |
| NEDg | Description generation | batch_69afcf12e3a0819098f28d31434a0c5f |
completed | March 10, 2026, 7:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afcf9c2d308190b111aa8038c9227a |
completed | March 10, 2026, 8 a.m. |
Created at: March 6, 2026, 9:59 p.m.