Triple
T37994026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Isabel–San Benito Navigation District |
E947893
|
entity |
| Predicate | hasTypeOfWaterway |
P27890
|
FINISHED |
| Object | Gulf Coast port |
—
|
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: Gulf Coast port | Statement: [Port Isabel–San Benito Navigation District, hasTypeOfWaterway, Gulf Coast port]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfWaterway Context triple: [Port Isabel–San Benito Navigation District, hasTypeOfWaterway, Gulf Coast port]
-
A.
hasWatercourseType
chosen
Indicates the specific kind or category of watercourse (such as river, stream, or canal) associated with an entity.
-
B.
isWaterway
Indicates that one entity is a water-based route or channel (such as a river, canal, or sea lane) used for travel or transport.
-
C.
hasWaterwayRole
Indicates that an entity participates in or is associated with a waterway in a specific functional capacity or role.
-
D.
waterwayClass
Indicates the classification or type of a waterway based on its navigational, functional, or physical characteristics.
-
E.
isInWaterwaySystem
Indicates that an entity is part of, contained within, or traverses a particular waterway network or system.
- 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_69f76efa37088190be5416b7ef1ca275 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a000014497c819088d5cda3977522dd |
completed | May 10, 2026, 3:48 a.m. |
| PD | Predicate disambiguation | batch_69ffff9a52b08190be1024e0fb6fe661 |
completed | May 10, 2026, 3:46 a.m. |
Created at: May 3, 2026, 4:20 p.m.