Triple
T1387960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Insurance Office |
E29888
|
entity |
| Predicate | canCollect |
P28195
|
FINISHED |
| Object | data from insurers and affiliates |
—
|
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: data from insurers and affiliates | Statement: [Federal Insurance Office, canCollect, data from insurers and affiliates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canCollect Context triple: [Federal Insurance Office, canCollect, data from insurers and affiliates]
-
A.
canHold
Indicates that one entity has the capacity or ability to contain, support, or carry another entity.
-
B.
canElect
Indicates that one entity has the authority or ability to choose another entity for a position, role, or office through an election process.
-
C.
canUse
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
-
D.
canBe
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
-
E.
canMake
Indicates that one entity has the ability or capacity to create, produce, or assemble another entity.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c35ad578819090abf96222112bda |
completed | March 1, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69a4beffcf808190ab4cd0271257ce63 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c2f16ae081908c92792253f3eb4b |
completed | March 1, 2026, 10:51 p.m. |
Created at: March 1, 2026, 7:59 p.m.