Triple
T352939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warsaw Telescope |
E7480
|
entity |
| Predicate | surveyMode |
P12155
|
FINISHED |
| Object | photometric survey |
—
|
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: photometric survey | Statement: [Warsaw Telescope, surveyMode, photometric survey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surveyMode Context triple: [Warsaw Telescope, surveyMode, photometric survey]
-
A.
hasDemographic
Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
-
B.
scrutinyMethods
Indicates the methods or procedures used to examine, inspect, or critically evaluate something.
-
C.
communicationMode
Indicates the method or channel through which communication between entities is carried out.
-
D.
screeningType
Indicates the specific method or category of screening applied in a screening process or evaluation.
-
E.
submissionType
Indicates the specific category or format under which something is submitted (e.g., as a document, assignment, application, or other submission class).
- 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.