Triple
T1336178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missouri–Kansas–Texas Railroad |
E28754
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Katy
Katy is the popular nickname for the Missouri–Kansas–Texas Railroad, a historic American railway that served the central and southern United States.
|
E154789
|
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: Katy | Statement: [Missouri–Kansas–Texas Railroad, shortName, Katy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katy Context triple: [Missouri–Kansas–Texas Railroad, shortName, Katy]
-
A.
Cowtown
Cowtown is a popular nickname for Calgary, a major Canadian city known for its historic cattle industry and annual Calgary Stampede.
-
B.
Lamar
Lamar is a surname most notably associated with Mirabeau B. Lamar, the second president of the Republic of Texas.
-
C.
Grand Tyler
Grand Tyler is a Masonic lodge officer responsible for guarding the entrance to the lodge and ensuring only duly qualified members are admitted.
-
D.
Grayson
Grayson is an unincorporated community located in Stanislaus County, California.
-
E.
McLendon-Chisholm, Texas
McLendon-Chisholm, Texas is a small, semi-rural city in the Dallas–Fort Worth metropolitan area known for its spacious residential developments and country-like setting.
- 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: Katy Triple: [Missouri–Kansas–Texas Railroad, shortName, Katy]
Generated description
Katy is the popular nickname for the Missouri–Kansas–Texas Railroad, a historic American railway that served the central and southern United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Katy Target entity description: Katy is the popular nickname for the Missouri–Kansas–Texas Railroad, a historic American railway that served the central and southern United States.
-
A.
Cowtown
Cowtown is a popular nickname for Calgary, a major Canadian city known for its historic cattle industry and annual Calgary Stampede.
-
B.
Lamar
Lamar is a surname most notably associated with Mirabeau B. Lamar, the second president of the Republic of Texas.
-
C.
Grand Tyler
Grand Tyler is a Masonic lodge officer responsible for guarding the entrance to the lodge and ensuring only duly qualified members are admitted.
-
D.
Grayson
Grayson is an unincorporated community located in Stanislaus County, California.
-
E.
McLendon-Chisholm, Texas
McLendon-Chisholm, Texas is a small, semi-rural city in the Dallas–Fort Worth metropolitan area known for its spacious residential developments and country-like setting.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1ecb5208190a9eadda113c91e66 |
completed | March 1, 2026, 10:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc62b9bd081909dbe22cbea03f21f |
completed | March 8, 2026, 12:43 a.m. |
| NEDg | Description generation | batch_69acc6c204a88190a3171898e6e1bb91 |
completed | March 8, 2026, 12:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acc7d8df108190bf92ca5e33987d04 |
completed | March 8, 2026, 12:50 a.m. |
Created at: March 1, 2026, 7:55 p.m.