Triple
T38024875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inspiration4 |
E948743
|
entity |
| Predicate | fundraisingOutcome |
P189869
|
FINISHED |
| Object | over US$200 million raised |
—
|
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 US$200 million raised | Statement: [Inspiration4, fundraisingOutcome, over US$200 million raised]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fundraisingOutcome Context triple: [Inspiration4, fundraisingOutcome, over US$200 million raised]
-
A.
donationResultedIn
Indicates that a donation directly caused or brought about a particular outcome or consequence.
-
B.
raisedMoneyFor
Indicates that one entity collected or obtained funds specifically to support or benefit another entity, cause, or purpose.
-
C.
GreatCauseOutcome
Indicates that a significant cause, action, or factor leads to a correspondingly major or impactful outcome.
-
D.
usesFundraisingMethod
Indicates that one entity employs or applies a particular fundraising method as its means of raising funds.
-
E.
fundraisingDescription
Indicates that a description or summary is provided for a fundraising activity, campaign, or effort involving the entities.
- F. None of above. chosen
Provenance (4 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_69f76efd1bc48190a729097fe5177b61 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbca6c066c8190a1599202f341417f |
completed | May 6, 2026, 11:10 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fbc993caa881908c16c3e21efaeef9 |
completed | May 6, 2026, 11:07 p.m. |
Created at: May 3, 2026, 4:20 p.m.