Triple
T19627737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Long |
E471181
|
entity |
| Predicate | donatedSalaryPortion |
P54997
|
FINISHED |
| Object | 2017 NFL season |
—
|
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: 2017 NFL season | Statement: [Chris Long, donatedSalaryPortion, 2017 NFL season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: donatedSalaryPortion Context triple: [Chris Long, donatedSalaryPortion, 2017 NFL season]
-
A.
beneficiaryContribution
Indicates that one party provides a contribution, support, or resources that benefit another designated beneficiary.
-
B.
donatedWith
Indicates that an entity made a donation using, accompanied by, or in association with a particular method, item, or context.
-
C.
donated
Indicates that one entity voluntarily gave something of value (such as money, goods, or time) to another entity, typically without expecting anything in return.
-
D.
philanthropicDonation
chosen
Indicates that one entity voluntarily gives money, goods, or services to another entity for charitable or public-benefit purposes without expecting direct compensation.
-
E.
donatedToState
Indicates that an entity has given or transferred something, such as money, goods, or assets, as a donation to a state or state-level governmental body.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640eadcc48190ab5e36ddcde0c328 |
completed | April 20, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69e514e5cb108190ae260e466c447314 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.