Triple
T68011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Education Center (United States Holocaust Memorial Museum) |
E1355
|
entity |
| Predicate | hasTypeOfProgram |
P2192
|
FINISHED |
| Object | teacher training 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: teacher training programs | Statement: [Education Center (United States Holocaust Memorial Museum), hasTypeOfProgram, teacher training programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfProgram Context triple: [Education Center (United States Holocaust Memorial Museum), hasTypeOfProgram, teacher training programs]
-
A.
programType
chosen
Indicates the category or kind of program to which an entity belongs or with which it is associated.
-
B.
hasPlatformType
Indicates that an entity is associated with or characterized by a specific type or category of platform.
-
C.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
D.
hasOnlinePrograms
Indicates that an entity offers or provides programs, courses, or services that are available online.
-
E.
hasOperationType
Indicates the specific kind or category of operation associated with an entity or process.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24ea8cfd081908a26edad2473dde3 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.