Triple
T9068245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Save America’s Treasures grants |
E217297
|
entity |
| Predicate | matchRatio |
P86776
|
FINISHED |
| Object | 1:1 non-federal to federal |
—
|
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: 1:1 non-federal to federal | Statement: [Save America’s Treasures grants, matchRatio, 1:1 non-federal to federal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchRatio Context triple: [Save America’s Treasures grants, matchRatio, 1:1 non-federal to federal]
-
A.
matchType
Indicates the specific category or nature of how two or more entities correspond or align with each other within a given context.
-
B.
matchResult
Indicates the outcome or final status produced by a particular match or game between participants.
-
C.
matchOf
Indicates that one entity is a specific match, counterpart, or corresponding instance of another entity within a defined context or set.
-
D.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
-
E.
matches
Indicates that two entities correspond to or are in agreement with each other according to some defined criteria or pattern.
- 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_69ca83d5a7f48190b16c1e59bd43ede0 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc94bf4f2881908c881e6ee7203994 |
completed | April 1, 2026, 3:45 a.m. |
| PD | Predicate disambiguation | batch_69cc65f881248190bfd220bb28a9fb5f |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc668ad3d881908a8a93a6a1d553e4 |
completed | April 1, 2026, 12:27 a.m. |
Created at: March 30, 2026, 7:11 p.m.