Triple
T35596642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 5 in Tukwila, Washington |
E1028649
|
entity |
| Predicate | isMajorBottleneck |
P115184
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Interstate 5 in Tukwila, Washington, isMajorBottleneck, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMajorBottleneck Context triple: [Interstate 5 in Tukwila, Washington, isMajorBottleneck, yes]
-
A.
isMajorBottleneckFor
chosen
Indicates that something significantly restricts or slows the progress, capacity, or performance of another process, system, or activity.
-
B.
isMajorFastAlongWith
Indicates that an entity is a primary or significant fast-moving element occurring together or in coordination with another entity.
-
C.
isMajor
Indicates that an entity holds primary or greater significance, importance, or rank relative to others in a given context.
-
D.
isMajorSeeWithin
Indicates that one entity is the primary or most significant location or area encompassed within the boundaries of another entity.
-
E.
isMajorFor
Indicates that one entity serves as the primary field of academic specialization (major) for another entity, typically a student.
- 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_69f76e0598dc8190a6a093e904b9aa70 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: May 3, 2026, 4:05 p.m.