Triple
T27047403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hours (film score) |
E684678
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object |
Clarissa Vaughan (character in The Hours)
Clarissa Vaughan is a central character in Michael Cunningham’s novel and its film adaptation "The Hours," a modern New York editor whose single day echoes Virginia Woolf’s Mrs. Dalloway as she prepares a party while confronting love, memory, and mortality.
|
E1757029
|
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: Clarissa Vaughan (character in The Hours) | Statement: [The Hours (film score), associatedWithCharacter, Clarissa Vaughan (character in The Hours)]
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: Clarissa Vaughan (character in The Hours) Triple: [The Hours (film score), associatedWithCharacter, Clarissa Vaughan (character in The Hours)]
Generated description
Clarissa Vaughan is a central character in Michael Cunningham’s novel and its film adaptation "The Hours," a modern New York editor whose single day echoes Virginia Woolf’s Mrs. Dalloway as she prepares a party while confronting love, memory, and mortality.
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_69ef148193c48190bb1a0cfae6a407c4 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f622acea248190a90c685058f42184 |
completed | May 2, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1247f5ce48819096dba2919e2b7901 |
completed | May 24, 2026, 12:36 a.m. |
| NEDg | Description generation | batch_6a1248e698008190b4e1d77080b52fef |
completed | May 24, 2026, 12:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1249ea67c8819092a4905943bd6e0e |
completed | May 24, 2026, 12:44 a.m. |
Created at: April 27, 2026, 8:11 a.m.