Triple
T352926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warsaw Telescope |
E7480
|
entity |
| Predicate | hasMount |
P12154
|
FINISHED |
| Object | equatorial mount |
—
|
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: equatorial mount | Statement: [Warsaw Telescope, hasMount, equatorial mount]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMount Context triple: [Warsaw Telescope, hasMount, equatorial mount]
-
A.
hasRegister
Indicates that one entity possesses, contains, or is associated with a specific register (such as a record, log, or hardware register).
-
B.
hasInitial
Indicates that one entity possesses or is associated with the first letter or starting character of another entity’s name or value.
-
C.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
-
D.
hasSummit
Indicates that one entity possesses, features, or includes a summit or highest point as part of its structure or characteristics.
-
E.
hasPar
Indicates a relationship where one entity has another entity as its parent.
- F. None of above. chosen
Provenance (4 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7f1be88190964ddcbb6a05f021 |
completed | Feb. 28, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69a2e9571bd88190b6fcb16f21604720 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0a4c448190a8a179daa9b90645 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.