Triple
T77734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nobel Prize in Physiology or Medicine |
E1554
|
entity |
| Predicate | firstAwardedFor |
P107
|
FINISHED |
| Object | work on serum therapy against diphtheria |
—
|
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: work on serum therapy against diphtheria | Statement: [Nobel Prize in Physiology or Medicine, firstAwardedFor, work on serum therapy against diphtheria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAwardedFor Context triple: [Nobel Prize in Physiology or Medicine, firstAwardedFor, work on serum therapy against diphtheria]
-
A.
firstAwarded
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
-
B.
awardFor
chosen
Indicates that something is given or granted as recognition or a prize for a particular achievement, work, or contribution.
-
C.
awardReceived
Indicates that an entity has been granted or honored with a specific award or recognition.
-
D.
lastAwarded
Indicates the most recent time or instance at which an entity received a particular award.
-
E.
isTheHighestAwardOf
Indicates that one award is the most prestigious or top-ranking honor within a particular field, organization, or context.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2559892dc81909303f2eefdc0025f |
completed | Feb. 28, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69a24eaf99e481908e8d314577e22ecf |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.