Triple
T29808151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The 2nd Law |
E756889
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Prelude
"Prelude" is the opening track of Muse's 2012 album *The 2nd Law*, serving as a brief orchestral introduction that sets the tone for the record.
|
E1887639
|
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: Prelude | Statement: [The 2nd Law, hasPart, Prelude]
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: Prelude Triple: [The 2nd Law, hasPart, Prelude]
Generated description
"Prelude" is the opening track of Muse's 2012 album *The 2nd Law*, serving as a brief orchestral introduction that sets the tone for the record.
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_69f2245584848190ad4cab1f07752ccb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6752c3da08190b114b1cddc9cc9d3 |
completed | May 2, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a26e5efab188190a082a5298ee66059 |
completed | June 8, 2026, 3:55 p.m. |
| NEDg | Description generation | batch_6a26e7ee6cb48190852a9e4071ab0a01 |
completed | June 8, 2026, 4:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a26e877559c81909febc9c4fbf2abaf |
completed | June 8, 2026, 4:06 p.m. |
Created at: April 29, 2026, 5:22 p.m.