Triple
T20472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Michigan |
E406
|
entity |
| Predicate | volume |
P1567
|
FINISHED |
| Object | about 4900 cubic kilometers |
—
|
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: about 4900 cubic kilometers | Statement: [Lake Michigan, volume, about 4900 cubic kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: volume Context triple: [Lake Michigan, volume, about 4900 cubic kilometers]
-
A.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
B.
width
Indicates the measurement of how wide an entity is, typically the extent of its horizontal dimension from side to side.
-
C.
vocalization
Indicates the act or manner of producing sounds or calls, typically as a means of communication.
-
D.
frequency
Indicates how often an event, action, or relationship occurs within a given period or context.
-
E.
tempo
Indicates the speed or pace at which an action, process, or sequence unfolds over time.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246f7bd30819085f751c41f6f029e |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246526f5881909bc2a46e978bd082 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246f4d7908190a947f6da251c6f3b |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.