Triple
T6908911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zariski topology |
E159881
|
entity |
| Predicate | onObject |
P43795
|
FINISHED |
| Object | Spec(R) |
—
|
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: Spec(R) | Statement: [Zariski topology, onObject, Spec(R)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onObject Context triple: [Zariski topology, onObject, Spec(R)]
-
A.
viewOnObject
Indicates that one entity directs its visual attention toward or observes another entity as an object of viewing.
-
B.
notableObject
Indicates that an entity is especially significant, famous, or noteworthy as an object in a given context or domain.
-
C.
viewOnObjects
Indicates a relationship where an entity directs its view or visual attention toward one or more objects.
-
D.
hasObject
Indicates that an entity is associated with or possesses a particular object as part of a relationship or action.
-
E.
mathematicalObject
chosen
Indicates that the subject is a mathematical entity or construct, such as a number, function, set, or structure, within a mathematical context.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9be98748190b5cb698e66e3aa42 |
completed | March 27, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:25 p.m.