Triple
T14447893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basic Attention Token |
E358253
|
entity |
| Predicate | icoFundsRaisedUSD |
P75026
|
FINISHED |
| Object | approximately 35 million |
—
|
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: approximately 35 million | Statement: [Basic Attention Token, icoFundsRaisedUSD, approximately 35 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: icoFundsRaisedUSD Context triple: [Basic Attention Token, icoFundsRaisedUSD, approximately 35 million]
-
A.
raisedMoneyFor
Indicates that one entity collected or obtained funds specifically to support or benefit another entity, cause, or purpose.
-
B.
approximateFundsRaised
chosen
Indicates an estimated amount of money that has been raised, rather than an exact or final total.
-
C.
seeksFundingFrom
Indicates that one entity is actively trying to obtain financial support or investment from another entity.
-
D.
peakAnnualFunding
Indicates the maximum amount of funding an entity receives in a single year within a given period.
-
E.
Pillar IIFundingMechanism
Indicates a funding-related relationship under Pillar II, specifying how financial resources are provided, structured, or allocated within that pillar’s framework.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9160126c8190a2862a1a3dde1aff |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c3a02fc819097373f97a260cdeb |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:19 a.m.