Triple
T164936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania Limited |
E2992
|
entity |
| Predicate | marketingDesignation |
P974
|
FINISHED |
| Object | premier train |
—
|
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: premier train | Statement: [Pennsylvania Limited, marketingDesignation, premier train]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marketingDesignation Context triple: [Pennsylvania Limited, marketingDesignation, premier train]
-
A.
hasDesignation
chosen
Indicates that an entity holds or is assigned a specific title, label, or formal designation.
-
B.
sharesDesignationTypeWith
Indicates that two entities have the same type or category of designation (e.g., title, label, or classification).
-
C.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
D.
brand
Indicates that one entity is the commercial brand or label under which another entity (such as a product, service, or organization) is marketed or identified.
-
E.
designUse
Indicates that one entity is used as a design basis, purpose, or intended functional use for another entity.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258827da481909b20ea5e9d21676f |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a25664ba8081908ac298511a9fc5ba |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.