Triple
T26515297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke Askew |
E669796
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
The Warrior and the Sorceress
The Warrior and the Sorceress is a 1984 low-budget sword-and-sorcery fantasy film loosely inspired by Akira Kurosawa’s Yojimbo, known for its desert setting, martial-arts action, and cult status among genre fans.
|
E1729802
|
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: The Warrior and the Sorceress | Statement: [Luke Askew, notableWork, The Warrior and the Sorceress]
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: The Warrior and the Sorceress Triple: [Luke Askew, notableWork, The Warrior and the Sorceress]
Generated description
The Warrior and the Sorceress is a 1984 low-budget sword-and-sorcery fantasy film loosely inspired by Akira Kurosawa’s Yojimbo, known for its desert setting, martial-arts action, and cult status among genre fans.
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_69eeb31b6dcc8190b30632dc3928a0c0 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f613bc641c819084343cc78d080640 |
completed | May 2, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11bb418f0c819087d0da0e73237015 |
completed | May 23, 2026, 2:35 p.m. |
| NEDg | Description generation | batch_6a11be62602081909cac24dd194530b4 |
completed | May 23, 2026, 2:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a11bee7bd508190a8d6a18cf0a238a1 |
completed | May 23, 2026, 2:51 p.m. |
Created at: April 27, 2026, 1:23 a.m.