Triple
T96897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Bridge monument in Concord |
E1951
|
entity |
| Predicate | touristType |
P1769
|
FINISHED |
| Object | heritage tourism |
—
|
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: heritage tourism | Statement: [North Bridge monument in Concord, touristType, heritage tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touristType Context triple: [North Bridge monument in Concord, touristType, heritage tourism]
-
A.
tourismType
chosen
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
B.
travelPreference
Indicates a person's favored way or style of traveling, such as preferred modes, conditions, or arrangements for trips.
-
C.
tourismRegion
Indicates that a place or area is designated or recognized as a tourism region associated with another geographic or administrative entity.
-
D.
isTouristDestination
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
-
E.
customerType
Indicates the classification or category assigned to a customer based on their characteristics, status, or relationship with a business.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.