Triple
T18244982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stellar Wind |
E436925
|
entity |
| Predicate | approximateEarnings |
P55500
|
FINISHED |
| Object | over 2 million US dollars |
—
|
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 2 million US dollars | Statement: [Stellar Wind, approximateEarnings, over 2 million US dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateEarnings Context triple: [Stellar Wind, approximateEarnings, over 2 million US dollars]
-
A.
careerEarningsApprox
chosen
Indicates an approximate total amount of money an entity has earned over the course of its career.
-
B.
approximateStipend
Indicates an estimated or rough amount of stipend associated with an entity or situation.
-
C.
approximatePurse
Indicates that one entity estimates or comes close to determining the value, amount, or contents of another entity’s purse or collection of resources.
-
D.
estimatedUsing
Indicates that one entity’s value, state, or outcome is derived by applying an estimation method, model, or procedure based on another entity.
-
E.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e6fbac8190bf252c4337f50c29 |
completed | April 19, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:33 a.m.