Triple
T35959132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Milwaukee |
E1039948
|
entity |
| Predicate | sankInBodyOfWater |
P116783
|
FINISHED |
| Object | Lake Michigan |
—
|
NE NERFINISHED |
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: Lake Michigan | Statement: [SS Milwaukee, sankInBodyOfWater, Lake Michigan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sankInBodyOfWater Context triple: [SS Milwaukee, sankInBodyOfWater, Lake Michigan]
-
A.
sunkInBodyOfWater
chosen
Indicates that an object or entity has gone beneath the surface and come to rest within a body of water.
-
B.
sankWhile
Indicates that one entity moved downward below a surface or level at the same time that another specified event or action was occurring.
-
C.
shipSankIn
Indicates that a specific ship sank (was lost or submerged) in a particular location or body of water.
-
D.
sunkDuring
Indicates that one entity was sunk in the course of, or as a result of, the event or time period represented by another entity.
-
E.
sankOn
Indicates that one entity moved downward and became submerged or lower in level relative to another entity or reference point.
- 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac23d1388190bdf9628b294943bd |
completed | May 3, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.