Triple
T16336336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaia Data Release 1 |
E396687
|
entity |
| Predicate | numberOfSources |
P62580
|
FINISHED |
| Object | >1000000000 |
—
|
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: >1000000000 | Statement: [Gaia Data Release 1, numberOfSources, >1000000000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSources Context triple: [Gaia Data Release 1, numberOfSources, >1000000000]
-
A.
numberOfPointSources
chosen
Indicates the total count of distinct point sources involved or present in a given context or system.
-
B.
requiresSources
Indicates that something must be supported, justified, or validated by one or more external sources.
-
C.
numberOfSites
Indicates the total count of distinct sites associated with or involved in the given entity or context.
-
D.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
E.
numberOfSeries
Indicates the total count of distinct series associated with or contained within 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4e3af7881908a3116c41ed69115 |
completed | April 17, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69e226eba9b48190af6e80d3d1c2aed3 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.