Triple
T33717512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert Schweitzer Hospital |
E863916
|
entity |
| Predicate | founderAwardYear |
P197639
|
FINISHED |
| Object | 1952 |
—
|
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: 1952 | Statement: [Albert Schweitzer Hospital, founderAwardYear, 1952]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: founderAwardYear Context triple: [Albert Schweitzer Hospital, founderAwardYear, 1952]
-
A.
hasFounderAward
Indicates that an entity has received an award specifically given to or associated with its founder.
-
B.
founderBirthYear
Indicates the year in which the founder of an entity was born.
-
C.
founderKnownFor
Indicates that a founder is particularly recognized or notable for a specific work, achievement, product, or contribution.
-
D.
wasFoundedBy
Indicates that an organization, institution, or entity came into existence through the initiating action or establishment by a specific founder or founding group.
-
E.
notableFounderAward
Indicates that an award is notably associated with the founder of an entity, typically recognizing the founder’s achievements or contributions.
- 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_69f34989871c81908682e22a2fe4b829 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
| PDg | Predicate description generation | batch_69fe9fb88db08190a8f4af350633330e |
completed | May 9, 2026, 2:45 a.m. |
Created at: May 1, 2026, 1:44 a.m.