Triple
T8528158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humboldt Township, Michigan |
E201871
|
entity |
| Predicate | hasManyLakes |
P83157
|
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: [Humboldt Township, Michigan, hasManyLakes, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasManyLakes Context triple: [Humboldt Township, Michigan, hasManyLakes, yes]
-
A.
numberOfLakes
Indicates the quantity of lakes associated with a given entity.
-
B.
hasLakeThatRepresents
Indicates a relationship where a lake serves as a symbolic or representative feature for something, such as a place, concept, or entity.
-
C.
hasMajorLake
Indicates that a geographic region or area contains at least one significant lake within its boundaries.
-
D.
connectsToByLake
Indicates that one entity is linked or joined to another specifically via a lake as the connecting medium or route.
-
E.
hasArtificialLakes
Indicates that one entity possesses, contains, or includes one or more man-made lakes within its area or domain.
- F. None of above. chosen
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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe672e0588190a84328e1bf974f08 |
completed | March 31, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69cbd111bf988190be98c92a607c6456 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe30d453481908f897ed2b06e7534 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:17 p.m.