Triple
T32031260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Campus |
E817964
|
entity |
| Predicate | geographicAttraction |
P7335
|
FINISHED |
| Object | students seeking to study in London |
—
|
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: students seeking to study in London | Statement: [London Campus, geographicAttraction, students seeking to study in London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicAttraction Context triple: [London Campus, geographicAttraction, students seeking to study in London]
-
A.
naturalAttractionOf
Indicates a relationship where one entity is a natural feature or site that draws interest, attention, or visitors from another entity.
-
B.
touristAttractionIn
chosen
Indicates that a place functions as a tourist attraction located within a specified geographic area or entity.
-
C.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
-
D.
notablePlace
Indicates that a place is especially significant, famous, or noteworthy in relation to the subject.
-
E.
ridesAttraction
Indicates that an entity participates in experiencing or using an attraction, such as going on a ride at a venue or amusement location.
- 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_69f348fbc8148190b3c0f95d4772b153 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 1, 2026, 12:18 a.m.