Triple
T35846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lincoln Memorial |
E709
|
entity |
| Predicate | visitorCountCategory |
P87
|
FINISHED |
| Object | one of the most visited monuments in the United States |
—
|
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: one of the most visited monuments in the United States | Statement: [Lincoln Memorial, visitorCountCategory, one of the most visited monuments in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visitorCountCategory Context triple: [Lincoln Memorial, visitorCountCategory, one of the most visited monuments in the United States]
-
A.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
-
B.
frequentlyVisitedBy
Indicates that an entity is regularly or often visited by another entity.
-
C.
hasVisitorType
Indicates the type or category of visitor associated with an entity (e.g., guest, customer, tourist, patient).
-
D.
visitedBy
Indicates that a location or entity is the destination or target of a visit performed by another entity.
-
E.
category
chosen
Indicates that one entity is classified as a member or type within the grouping or class defined by 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24bb753f081909cd8b25cfb8e08af |
completed | Feb. 28, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69a24ab4a6908190b6f355415ffe7948 |
completed | Feb. 28, 2026, 1:53 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.