Triple
T36991768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | downtown Seattle and University of Washington |
E915120
|
entity |
| Predicate | frequentlyTraversedBy |
P54144
|
FINISHED |
| Object | students |
—
|
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 | Statement: [downtown Seattle and University of Washington, frequentlyTraversedBy, students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentlyTraversedBy Context triple: [downtown Seattle and University of Washington, frequentlyTraversedBy, students]
-
A.
frequentlyVisitedBy
Indicates that an entity is regularly or often visited by another entity.
-
B.
frequentlyUsedBy
Indicates that something is regularly or commonly utilized by a particular entity.
-
C.
isFrequentlyReferencedAs
Indicates that one entity is commonly or repeatedly mentioned, cited, or referred to by another entity or within a particular context.
-
D.
frequentlySeen
Indicates that one entity is observed or encountered many times or on a regular basis in relation to another entity.
-
E.
travelsThrough
chosen
Indicates that something moves along, passes across, or is routed via a particular path, medium, or 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:14 p.m.