Triple
T22268297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Rosa Wall |
E550406
|
entity |
| Predicate | hasDropOffDepth |
P147612
|
FINISHED |
| Object | greater than 30 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: greater than 30 meters | Statement: [Santa Rosa Wall, hasDropOffDepth, greater than 30 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDropOffDepth Context triple: [Santa Rosa Wall, hasDropOffDepth, greater than 30 meters]
-
A.
hasBerthDepth
Indicates the depth of water available at a specific berth where a vessel can be moored.
-
B.
hasDropOffArea
Indicates that an entity provides a designated area where items, passengers, or goods can be temporarily left or unloaded.
-
C.
hasWaterDepthAtExit
Indicates the water depth measured at the exit point of a structure, channel, or system.
-
D.
hasWaterDepthCategory
Indicates the classification of something based on the range or category of its water depth.
-
E.
hasDivingDepth
Indicates that an entity is associated with a specific depth to which it can or does dive.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141bd0ea88190b3574883b695d56c |
completed | April 28, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69e72ff0363081909f794d19c8a64837 |
completed | April 21, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e7342ce08c8190bc0a7085f4a952e7 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 8:39 p.m.