Triple
T3631125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kepler space telescope |
E76957
|
entity |
| Predicate | monitoredNumberOfStars |
P7300
|
FINISHED |
| Object | over 150000 |
—
|
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: over 150000 | Statement: [Kepler space telescope, monitoredNumberOfStars, over 150000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monitoredNumberOfStars Context triple: [Kepler space telescope, monitoredNumberOfStars, over 150000]
-
A.
starCount
Indicates the number of stars associated with an entity, typically representing a rating, quality level, or count of starred items.
-
B.
hasStarOn
Indicates that one entity bears or displays a star symbol positioned on another entity.
-
C.
numberOfStarsInConstellation
Indicates the numerical count of stars that belong to a given constellation.
-
D.
approximateStellarCount
chosen
Indicates an estimated or rough number of stars associated with a given astronomical object or region.
-
E.
numberOfBrightNakedEyeStars
Indicates the count of stars that are bright enough to be seen with the naked eye.
- 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_69ad85dc03948190b35b7189e4175bcc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc30136e88190922bb542971b5239 |
completed | March 8, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69adb8410a5881909c94818d7060b2b0 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:23 p.m.