Triple
T3461438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badaling |
E73033
|
entity |
| Predicate | visitorPopularity |
P20205
|
FINISHED |
| Object | major domestic tourist destination |
—
|
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: major domestic tourist destination | Statement: [Badaling, visitorPopularity, major domestic tourist destination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visitorPopularity Context triple: [Badaling, visitorPopularity, major domestic tourist destination]
-
A.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
-
B.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
-
C.
hasTouristPopularity
chosen
Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
-
D.
visitorAttractionRank
Indicates the relative ranking or position of a visitor attraction compared to other attractions, typically based on popularity, quality, or importance.
-
E.
visitorStatus
Indicates the current state or condition of an entity in its role as a visitor (e.g., whether they are active, pending, past, or otherwise classified in their visit).
- 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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae745e081909007cd3a664c57f3 |
completed | March 8, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69adae05bb0081909dc7e4779d6e05ef |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.