Triple
T20403699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triangulum |
E500404
|
entity |
| Predicate | hasBayerStars |
P140008
|
FINISHED |
| Object | about 10 |
—
|
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: about 10 | Statement: [Triangulum, hasBayerStars, about 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBayerStars Context triple: [Triangulum, hasBayerStars, about 10]
-
A.
hasBrightSpots
Indicates that an entity possesses one or more areas or points that are noticeably brighter than their surroundings.
-
B.
isBrightStar
Indicates that the subject star has a high intrinsic luminosity or apparent brightness compared to typical stars.
-
C.
hasBrightStar
Indicates that one entity possesses, contains, or is associated with a star characterized by high brightness.
-
D.
hasBrightStarDesignation
Indicates that an entity is assigned a specific identifier in the Bright Star Catalogue.
-
E.
visibleInLongExposureImages
Indicates that the subject can be detected or seen when images are captured using long exposure photography settings.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6799080cc819096dc31f41d1d7b49 |
completed | April 20, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69e5765d7cb48190adec18d6d1e3d263 |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:29 a.m.