Triple
T152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Science, The Endless Frontier |
E2
|
entity |
| Predicate | impact |
P9
|
FINISHED |
| Object | shaped federal-university research partnership in the United States |
—
|
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: shaped federal-university research partnership in the United States | Statement: [Science, The Endless Frontier, impact, shaped federal-university research partnership in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impact Context triple: [Science, The Endless Frontier, impact, shaped federal-university research partnership in the United States]
-
A.
influenced
chosen
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
B.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
C.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
-
D.
employer
Indicates a relationship where one entity hires, pays, and oversees the work of another entity.
-
E.
genre
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
- 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_69a222a954e48190b48f126a67485661 |
completed | Feb. 27, 2026, 11:03 p.m. |
| NER | Named-entity recognition | batch_69a2266edf048190828e8f53cb7f6ba6 |
completed | Feb. 27, 2026, 11:19 p.m. |
| PD | Predicate disambiguation | batch_69a222f9916081908db2eedc81d85301 |
completed | Feb. 27, 2026, 11:04 p.m. |
Created at: Feb. 27, 2026, 11:04 p.m.