Triple
T10852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Holocaust Memorial Museum |
E220
|
entity |
| Predicate | hasVisitorType |
P1284
|
FINISHED |
| Object | domestic visitors |
—
|
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: domestic visitors | Statement: [United States Holocaust Memorial Museum, hasVisitorType, domestic visitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisitorType Context triple: [United States Holocaust Memorial Museum, hasVisitorType, domestic visitors]
-
A.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
B.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
-
C.
hasTypeOfRecipient
Indicates that an entity is associated with a specific category or kind of recipient it is intended for or directed to.
-
D.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
E.
hasCollectionType
Indicates that an entity is associated with or organized under a specific type or category of collection.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a242cd8fb481909562f114f4ce7700 |
completed | Feb. 28, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69a23fe6b0bc8190bcce9b74f2c5fb08 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a242cce40481908e5eae0c94313c25 |
completed | Feb. 28, 2026, 1:20 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.