Triple
T3591902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Tampa |
E76043
|
entity |
| Predicate | waterDepthCharacteristic |
P42757
|
FINISHED |
| Object | deep-water channel suitable for large vessels |
—
|
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: deep-water channel suitable for large vessels | Statement: [Port of Tampa, waterDepthCharacteristic, deep-water channel suitable for large vessels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterDepthCharacteristic Context triple: [Port of Tampa, waterDepthCharacteristic, deep-water channel suitable for large vessels]
-
A.
hasWaterDepthCategory
chosen
Indicates the classification of something based on the range or category of its water depth.
-
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.
maximumWaterDepth
Indicates the greatest depth of water present or allowed in a given context, such as a location, container, or body of water.
-
D.
seaDepth
Indicates the measured vertical distance from the sea surface down to the seafloor at a given location.
-
E.
seaDepthRange
Indicates the minimum and maximum water depth values associated with a given sea or marine location.
- 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_69ad85d8042081908af94a04c410dec0 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc15a546481909c72dac80d65e1fb |
completed | March 8, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69adb839b4e08190b1c0d611cccb11ae |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:22 p.m.