Triple
T35953215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Resolution Funding Corporation |
E1039784
|
entity |
| Predicate | roleInCrisisManagement |
P202085
|
FINISHED |
| Object | financing thrift resolutions |
—
|
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: financing thrift resolutions | Statement: [Resolution Funding Corporation, roleInCrisisManagement, financing thrift resolutions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInCrisisManagement Context triple: [Resolution Funding Corporation, roleInCrisisManagement, financing thrift resolutions]
-
A.
roleInDisasterPrevention
Indicates that an entity has a specific function, responsibility, or involvement in activities aimed at preventing or mitigating disasters.
-
B.
roleInRescue
Indicates the specific function or responsibility an entity has within a rescue operation or event.
-
C.
roleInIncident
chosen
Indicates the specific function, capacity, or involvement an entity has within a particular incident or event.
-
D.
roleInHazard
Indicates a specific function, responsibility, or involvement that an entity has within the context of a particular hazard or hazardous situation.
-
E.
roleInDisasterMovie
Indicates that an entity has a specific acting or production role in a disaster-themed movie.
- 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_69f76e25ea488190b7cee970b3e70382 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a016b2629c48190befb10581560d58f |
completed | May 11, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_6a0167d5a2088190a68dbd2b87f73e80 |
completed | May 11, 2026, 5:23 a.m. |
Created at: May 3, 2026, 4:07 p.m.