Triple
T7340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Advanced Technological Education |
E144
|
entity |
| Predicate | beneficiary |
P487
|
FINISHED |
| Object | students in technician programs |
—
|
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: students in technician programs | Statement: [Advanced Technological Education, beneficiary, students in technician programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beneficiary Context triple: [Advanced Technological Education, beneficiary, students in technician programs]
-
A.
benefitedCountry
Indicates that one country gains an advantage, profit, or positive outcome from an action, event, or entity associated with another.
-
B.
notableRecipient
Indicates that an entity has received a notable award, honor, or recognition from another entity.
-
C.
benefits
chosen
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
D.
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.
-
E.
fundedBy
Indicates that an entity receives financial support or resources from another entity.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a241a55ac081909e95b71c97db8140 |
completed | Feb. 28, 2026, 1:15 a.m. |
| PD | Predicate disambiguation | batch_69a23fe1cf38819080ea56c40bf2632e |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.