Triple
T252559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marquette, Michigan |
E5180
|
entity |
| Predicate | hasHarborFunction |
P6668
|
FINISHED |
| Object | iron ore shipping |
—
|
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: iron ore shipping | Statement: [Marquette, Michigan, hasHarborFunction, iron ore shipping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHarborFunction Context triple: [Marquette, Michigan, hasHarborFunction, iron ore shipping]
-
A.
hasHarbor
Indicates that a place possesses or contains a harbor for docking or sheltering vessels.
-
B.
harborType
chosen
Indicates the specific kind or classification of a harbor associated with an entity.
-
C.
harbor
Indicates providing shelter, protection, or refuge for someone or something, often by keeping them in a safe or hidden place.
-
D.
hasShoreFeature
Indicates that a shore or coastline possesses a specific physical or environmental feature.
-
E.
hasReserveFunction
Indicates that an entity serves as a backup or secondary option that can perform the same function if the primary one is unavailable or fails.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d39eb3881909f435043c8697f13 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b678d6c81909780e1995c1ca691 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.