Triple
T4920712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TT |
E110456
|
entity |
| Predicate | spectatorAttraction |
P5644
|
FINISHED |
| Object | draws tens of thousands of visitors annually |
—
|
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: draws tens of thousands of visitors annually | Statement: [TT, spectatorAttraction, draws tens of thousands of visitors annually]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spectatorAttraction Context triple: [TT, spectatorAttraction, draws tens of thousands of visitors annually]
-
A.
attractionType
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
-
B.
isMajorAttractionFor
chosen
Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
-
C.
partOfAttractionType
Indicates that one attraction type is a component or subset of a broader, more general attraction type.
-
D.
isAttractionFor
Indicates that one entity serves as an attraction or point of interest specifically intended for another entity (such as a person, group, or audience).
-
E.
ticketedAttraction
Indicates that access to the attraction requires a purchased ticket or paid admission.
- 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_69bd4413f9908190afcff44d7929cc4c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffabccc81909115ece1b04e2061 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3421588190ab08e92b9558042e |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:30 p.m.