Triple
T30387604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outreachy |
E772989
|
entity |
| Predicate | compensatesWith |
P72053
|
FINISHED |
| Object | stipend |
—
|
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: stipend | Statement: [Outreachy, compensatesWith, stipend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compensatesWith Context triple: [Outreachy, compensatesWith, stipend]
-
A.
compensated
Indicates that one entity provides payment or some form of recompense to another entity in return for goods, services, or loss incurred.
-
B.
compensatoryType
Indicates the specific category or nature of compensation associated with an action, obligation, or remedy in the relationship.
-
C.
compensationMechanism
chosen
Indicates a relationship where one entity provides payment, benefits, or other forms of recompense to another in return for a loss, service, or obligation.
-
D.
compensationTrigger
Indicates the event or condition that initiates or authorizes a compensation or payment to be made.
-
E.
compensationReason
Indicates the reason or cause for which compensation is granted, requested, or applied between entities.
- 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_69f2248ef0a48190aa54d4d8ac3e5758 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 29, 2026, 8:01 p.m.