Triple
T33781067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lazarus Project |
E865656
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Charly Clive
Charly Clive is a British actress and comedian best known for her lead role in the TV series "Pure" and her performance in the sci-fi thriller series "The Lazarus Project."
|
E2067650
|
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: Charly Clive | Statement: [The Lazarus Project, stars, Charly Clive]
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: Charly Clive Triple: [The Lazarus Project, stars, Charly Clive]
Generated description
Charly Clive is a British actress and comedian best known for her lead role in the TV series "Pure" and her performance in the sci-fi thriller series "The Lazarus Project."
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_69f3498ecc2c8190bcd85e3f11dc215e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fcc8b3bc8190939a334c23e2ffa2 |
completed | May 3, 2026, 7:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3665898d1481908913411737110016 |
completed | June 20, 2026, 10:03 a.m. |
| NEDg | Description generation | batch_6a36663e473c81908cb06cf9eb79cfc0 |
completed | June 20, 2026, 10:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3666ebe7ec8190a279f7eb183cf157 |
completed | June 20, 2026, 10:09 a.m. |
Created at: May 1, 2026, 1:45 a.m.