Triple
T16621713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaia Data Release 3 |
E403847
|
entity |
| Predicate | approximateNumberOfAstrometricSources |
P62580
|
FINISHED |
| Object | 1.5 billion |
—
|
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: 1.5 billion | Statement: [Gaia Data Release 3, approximateNumberOfAstrometricSources, 1.5 billion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfAstrometricSources Context triple: [Gaia Data Release 3, approximateNumberOfAstrometricSources, 1.5 billion]
-
A.
approximateStellarCount
Indicates an estimated or rough number of stars associated with a given astronomical object or region.
-
B.
numberOfPointSources
chosen
Indicates the total count of distinct point sources involved or present in a given context or system.
-
C.
possibleAstrometricDetection
Indicates that there is a potential, but not yet fully confirmed, detection of an object or phenomenon based on astrometric measurements of its position or motion.
-
D.
approximateNumberOfGalaxies
Indicates an estimated or roughly calculated count of galaxies associated with a given subject.
-
E.
numberOfSatellites
Indicates the quantity of satellites that are associated with or orbit a given entity.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754e80ec8190b3c66b33dbc7463c |
completed | April 18, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e296ad3f148190af09223dc35b155c |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.