Triple
T328317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania Station (Baltimore) |
E6568
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object |
BAL
BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
|
E41917
|
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: BAL | Statement: [Pennsylvania Station (Baltimore), stationCode, BAL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BAL Context triple: [Pennsylvania Station (Baltimore), stationCode, BAL]
-
A.
BEL
BEL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Belgium in international standards and data systems.
-
B.
BA
BA is the New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
-
C.
BOL
BOL is the three-letter ISO 3166-1 alpha-3 country code assigned to Bolivia.
-
D.
BO
BO is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Bolivia in international standards and systems.
-
E.
AL
AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
- 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: BAL Triple: [Pennsylvania Station (Baltimore), stationCode, BAL]
Generated description
BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BAL Target entity description: BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
-
A.
BEL
BEL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Belgium in international standards and data systems.
-
B.
BA
BA is the New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
-
C.
BOL
BOL is the three-letter ISO 3166-1 alpha-3 country code assigned to Bolivia.
-
D.
BO
BO is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Bolivia in international standards and systems.
-
E.
AL
AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eaad37b0819085beda2a491da9a8 |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3cfef5f4c8190a9c0e14a5a501237 |
completed | March 1, 2026, 5:34 a.m. |
| NEDg | Description generation | batch_69a3d068ea8c81908851444ca70a64b4 |
completed | March 1, 2026, 5:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3d0eb96748190aa8c47736820387c |
completed | March 1, 2026, 5:38 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.