Triple
T16991808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fifty-Nine Icosahedra |
E412210
|
entity |
| Predicate | numberOfStellationsClassified |
P126079
|
FINISHED |
| Object | 59 |
—
|
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: 59 | Statement: [The Fifty-Nine Icosahedra, numberOfStellationsClassified, 59]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStellationsClassified Context triple: [The Fifty-Nine Icosahedra, numberOfStellationsClassified, 59]
-
A.
numberOfStarsInConstellation
Indicates the numerical count of stars that belong to a given constellation.
-
B.
numberOfConstellations
Indicates the total count of constellations associated with a given subject.
-
C.
numberOfCentralStars
Indicates the quantity of central stars associated with or contained within a given entity or system.
-
D.
approximateStellarCount
Indicates an estimated or rough number of stars associated with a given astronomical object or region.
-
E.
starCount
Indicates the number of stars associated with an entity, typically representing a rating, quality level, or count of starred items.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d280e3348190a27bd5dc7cf87c0e |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e378e037c88190935d732e0f10d5d7 |
completed | April 18, 2026, 12:28 p.m. |
Created at: April 10, 2026, 5:32 a.m.