Triple
T10991972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hirzebruch–Riemann–Roch theorem |
E259772
|
entity |
| Predicate | domainObject |
P16979
|
FINISHED |
| Object | compact complex manifold X |
—
|
LITERAL 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: compact complex manifold X | Statement: [Hirzebruch–Riemann–Roch theorem, domainObject, compact complex manifold X]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: domainObject Context triple: [Hirzebruch–Riemann–Roch theorem, domainObject, compact complex manifold X]
-
A.
typicalObjectType
Indicates that something is a common or characteristic type of object typically associated with or involved in another entity or situation.
-
B.
notableObject
Indicates that an entity is especially significant, famous, or noteworthy as an object in a given context or domain.
-
C.
viewOnObject
Indicates that one entity directs its visual attention toward or observes another entity as an object of viewing.
-
D.
notableObjectOfStudy
chosen
Indicates that a subject is a significant or prominent focus of research, analysis, or scholarly attention for another entity.
-
E.
viewOnObjects
Indicates a relationship where an entity directs its view or visual attention toward one or more objects.
- F. None of above.
Provenance (3 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d795d1e918819090c71f5a077fa15a |
completed | April 9, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69d72e93ac648190b46c5d12bf3eb1e9 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.