Triple
T36655069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madeleine Sami |
E904965
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
The Bad Seed
The Bad Seed is a New Zealand television comedy-drama series in which Madeleine Sami plays a prominent role.
|
E2194465
|
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 Bad Seed | Statement: [Madeleine Sami, notableWork, The Bad Seed]
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 Bad Seed Triple: [Madeleine Sami, notableWork, The Bad Seed]
Generated description
The Bad Seed is a New Zealand television comedy-drama series in which Madeleine Sami plays a prominent role.
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_69f76e6e3b908190970251b30f76ad71 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c736357881909b45b2069eec1d0c |
completed | May 3, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3a20ccebbc819095befd25c26537c8 |
completed | June 23, 2026, 5:59 a.m. |
| NEDg | Description generation | batch_6a3a2192adb8819089291a4deb8a7f12 |
completed | June 23, 2026, 6:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3a23d1bfc0819092d83bc795391504 |
completed | June 23, 2026, 6:12 a.m. |
Created at: May 3, 2026, 4:11 p.m.