Triple
T24420285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexican Pacific ports system |
E615704
|
entity |
| Predicate | includesTypeOfPort |
P16380
|
FINISHED |
| Object | commercial seaports |
—
|
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: commercial seaports | Statement: [Mexican Pacific ports system, includesTypeOfPort, commercial seaports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesTypeOfPort Context triple: [Mexican Pacific ports system, includesTypeOfPort, commercial seaports]
-
A.
includesPort
Indicates that one entity contains, encompasses, or has as part of it a specific port or set of ports.
-
B.
hasPortType
chosen
Indicates that an entity is associated with, or characterized by, a specific type or category of port.
-
C.
isInPort
Indicates that an entity (such as a vessel or vehicle) is currently located within or docked at a specific port.
-
D.
hasPortOn
Indicates that one entity possesses or is located adjacent to a port situated on another specified geographic or infrastructural feature (such as a coast, river, or lake).
-
E.
hasPortSpecialization
Indicates that an entity has a specific functional or technical specialization related to a port or interface.
- 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_69e2d7e9bfac8190a748952a90957106 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296a227d08190bd4e3e4832c5a205 |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:14 a.m.