Triple
T27715508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hilary Knight |
E698804
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Nina, Nina Ballerina
"Nina, Nina Ballerina" is a children's picture book about a young aspiring ballerina, illustrated (and often associated) with the whimsical, detailed style of artist Hilary Knight.
|
E1785110
|
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: Nina, Nina Ballerina | Statement: [Hilary Knight, notableWork, Nina, Nina Ballerina]
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: Nina, Nina Ballerina Triple: [Hilary Knight, notableWork, Nina, Nina Ballerina]
Generated description
"Nina, Nina Ballerina" is a children's picture book about a young aspiring ballerina, illustrated (and often associated) with the whimsical, detailed style of artist Hilary Knight.
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_69ef590f655c81909f93893b3b3219b2 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f635cfa6088190aae92d408c036238 |
completed | May 2, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a12e46395e48190bcf054f958449f0c |
completed | May 24, 2026, 11:43 a.m. |
| NEDg | Description generation | batch_6a12e528463c819087d479b960e660d2 |
completed | May 24, 2026, 11:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a12e58a24a08190baec56a49e9f24e8 |
completed | May 24, 2026, 11:48 a.m. |
Created at: April 27, 2026, 3:04 p.m.