Triple
T33943258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langlands dual group |
E870220
|
entity |
| Predicate | correspondsTo |
P6530
|
FINISHED |
| Object |
Langlands parameters
Langlands parameters are homomorphisms from a local or global Galois or Weil(-Deligne) group into the Langlands dual group that encode how automorphic representations correspond to Galois representations in the Langlands program.
|
E2074820
|
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: Langlands parameters | Statement: [Langlands dual group, correspondsTo, Langlands parameters]
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: Langlands parameters Triple: [Langlands dual group, correspondsTo, Langlands parameters]
Generated description
Langlands parameters are homomorphisms from a local or global Galois or Weil(-Deligne) group into the Langlands dual group that encode how automorphic representations correspond to Galois representations in the Langlands program.
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_69f3499b0dd48190b07b4b60babcee02 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70237574c8190b06ebb9a446fece4 |
completed | May 3, 2026, 8:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3689d7790c819085b52b6e52b40c59 |
completed | June 20, 2026, 12:38 p.m. |
| NEDg | Description generation | batch_6a368a5f070c81909a5d0e8f4ac5ad2e |
completed | June 20, 2026, 12:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a368b17fd848190be803db49a0ef089 |
completed | June 20, 2026, 12:44 p.m. |
Created at: May 1, 2026, 1:49 a.m.