Triple
T37053436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonneville International |
E917108
|
entity |
| Predicate | notableStationClusterLocation |
P203901
|
FINISHED |
| Object | Salt Lake City market |
E2210265
|
NE 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: Salt Lake City market | Statement: [Bonneville International, notableStationClusterLocation, Salt Lake City market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableStationClusterLocation Context triple: [Bonneville International, notableStationClusterLocation, Salt Lake City market]
-
A.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
B.
notableShowLocation
Indicates that a show or performance is notably associated with, took place at, or is best known for occurring in a particular location.
-
C.
notableLocationOn
chosen
Indicates that a particular location is especially significant or noteworthy in relation to a specified entity or context.
-
D.
notableLocationFeatured
Indicates that a particular location is prominently highlighted or showcased in relation to the subject.
-
E.
notableLocationFeature
Indicates that a location is characterized or distinguished by a particular notable physical or contextual feature.
- F. None of above.
Provenance (4 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_69f76e94d0308190a3f06890e133c88e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3efdb86e88819081b53c75ba5437bb |
completed | June 26, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:14 p.m.