Triple
T1607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Academy of Sciences |
E30
|
entity |
| Predicate | fundingSource |
P67
|
FINISHED |
| Object | federal government contracts |
—
|
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: federal government contracts | Statement: [National Academy of Sciences, fundingSource, federal government contracts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fundingSource Context triple: [National Academy of Sciences, fundingSource, federal government contracts]
-
A.
fundedBy
chosen
Indicates that an entity receives financial support or resources from another entity.
-
B.
fundingModel
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
-
C.
funds
Indicates that one entity provides financial resources or monetary support to another entity or activity.
-
D.
endowmentCurrency
Indicates the type of currency in which an endowment is denominated or valued.
-
E.
capital
Indicates that one place serves as the official seat of government or primary administrative center for another political 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a23344daf8819083118bbac5f46568 |
completed | Feb. 28, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69a232e52e7c81909c072703e28e8c61 |
completed | Feb. 28, 2026, 12:12 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.