Triple
T106489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union Pacific Railroad |
E2147
|
entity |
| Predicate | reportingMarks |
P2130
|
FINISHED |
| Object |
UPY
UPY is a reporting mark used by Union Pacific Railroad, primarily identifying its yard and switching locomotives.
|
E11065
|
NE FINISHED |
How this triple was built (4 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: UPY | Statement: [Union Pacific Railroad, reportingMarks, UPY]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UPY Context triple: [Union Pacific Railroad, reportingMarks, UPY]
-
A.
UP
UP is the standard reporting mark used to identify rail equipment owned or operated by the Union Pacific Railroad in North America.
-
B.
HUP
HUP is a major academic medical center in Philadelphia that serves as the flagship teaching hospital of the University of Pennsylvania's health system.
-
C.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
D.
LBY
LBY is the three-letter ISO 3166-1 alpha-3 country code assigned to Libya.
-
E.
U4 Network
U4 Network is an international alliance of research-intensive universities that collaborate closely on education, research, and academic exchange.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: UPY Triple: [Union Pacific Railroad, reportingMarks, UPY]
Generated description
UPY is a reporting mark used by Union Pacific Railroad, primarily identifying its yard and switching locomotives.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: UPY Target entity description: UPY is a reporting mark used by Union Pacific Railroad, primarily identifying its yard and switching locomotives.
-
A.
UP
UP is the standard reporting mark used to identify rail equipment owned or operated by the Union Pacific Railroad in North America.
-
B.
HUP
HUP is a major academic medical center in Philadelphia that serves as the flagship teaching hospital of the University of Pennsylvania's health system.
-
C.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
D.
LBY
LBY is the three-letter ISO 3166-1 alpha-3 country code assigned to Libya.
-
E.
U4 Network
U4 Network is an international alliance of research-intensive universities that collaborate closely on education, research, and academic exchange.
- F. None of above. chosen
Provenance (5 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25b7e2c188190b1dd8aafd4507a99 |
completed | Feb. 28, 2026, 3:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a275e644a48190aa2b8cb142b14394 |
completed | Feb. 28, 2026, 4:58 a.m. |
| NEDg | Description generation | batch_69a276cddee08190aab0959702d44f67 |
completed | Feb. 28, 2026, 5:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a277b7aee8819085cb05afc213eaff |
completed | Feb. 28, 2026, 5:05 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.