Triple
T17072236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Francisco Maru |
E414250
|
entity |
| Predicate | bowDepth |
P125749
|
FINISHED |
| Object | approximately 52 meters |
—
|
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: approximately 52 meters | Statement: [San Francisco Maru, bowDepth, approximately 52 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bowDepth Context triple: [San Francisco Maru, bowDepth, approximately 52 meters]
-
A.
drillDepth
Indicates the measured or specified depth to which a drilling operation extends into a material or medium.
-
B.
riverbedDepth
Indicates the depth or vertical distance from the water surface to the bottom of a river at a given location or time.
-
C.
saddleDepth
Indicates the measured vertical distance or depth of a saddle-shaped feature between its highest surrounding points.
-
D.
depthMetresApprox
Indicates an approximate measurement of how deep something is in metres, rather than an exact value.
-
E.
depth
Indicates the vertical distance from a reference surface or top point down to a lower point or bottom within a medium or space.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbc1b7d48190979a848b4188cb22 |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:34 a.m.