Triple
T24337103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bochner–Kodaira–Nakano identity |
E613409
|
entity |
| Predicate | involves |
P1256
|
FINISHED |
| Object |
Dolbeault Laplacian
The Dolbeault Laplacian is a differential operator on complex manifolds that acts on differential forms to study their cohomology and harmonic representatives in complex geometry.
|
E1627562
|
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: Dolbeault Laplacian | Statement: [Bochner–Kodaira–Nakano identity, involves, Dolbeault Laplacian]
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: Dolbeault Laplacian Triple: [Bochner–Kodaira–Nakano identity, involves, Dolbeault Laplacian]
Generated description
The Dolbeault Laplacian is a differential operator on complex manifolds that acts on differential forms to study their cohomology and harmonic representatives in complex geometry.
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_69e2d7dcc5a08190b53691130d56cbc4 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293212a0881908da028e81d26247d |
completed | April 29, 2026, 11:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0fc9efd0c881909b94dcb63ec08d47 |
completed | May 22, 2026, 3:13 a.m. |
| NEDg | Description generation | batch_6a0fcc23ef5481909836d7e07a705a31 |
completed | May 22, 2026, 3:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0fcc90fcbc8190a5a41d17f10c09e5 |
completed | May 22, 2026, 3:25 a.m. |
Created at: April 18, 2026, 1:57 a.m.