Triple
T31016096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heroic Naval Military School |
E790330
|
entity |
| Predicate | trainsForServiceIn |
P14268
|
FINISHED |
| Object | Mexican Navy |
—
|
NE NERFINISHED |
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: Mexican Navy | Statement: [Heroic Naval Military School, trainsForServiceIn, Mexican Navy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainsForServiceIn Context triple: [Heroic Naval Military School, trainsForServiceIn, Mexican Navy]
-
A.
trainsOn
Indicates that one entity receives training, instruction, or practice using or based on another entity (such as a resource, dataset, tool, or subject).
-
B.
maintainsTrainsFor
Indicates that one entity is responsible for servicing, repairing, or otherwise keeping trains operational for another entity.
-
C.
servedByNamedTrain
Indicates that a service, route, or journey is operated specifically by a train with a particular designated name.
-
D.
trainsForOccupation
chosen
Indicates that an entity undergoes training or preparation aimed at qualifying for or performing a specific occupation.
-
E.
hasRailServiceAt
Indicates that a rail transport service operates at or serves a particular location or facility.
- 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_69f224c811508190a7de096a5b1f5798 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6c1bb5f248190834161b5a6ba1ece |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 29, 2026, 8:57 p.m.