Triple
T3597679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTA Pink Line |
E76177
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Ashland
Ashland is a Chicago 'L' rapid transit station on the CTA's Pink Line serving the city's Near West Side.
|
E372120
|
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: Ashland | Statement: [CTA Pink Line, hasStation, Ashland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashland Context triple: [CTA Pink Line, hasStation, Ashland]
-
A.
Ashland
Ashland is an unincorporated community in Alameda County, California, situated in the East Bay region of the San Francisco Bay Area.
-
B.
Ashland, Ohio
Ashland, Ohio is a small city in north-central Ohio known historically as a regional manufacturing and agricultural center and home to Ashland University.
-
C.
Ashland, Kentucky
Ashland, Kentucky is a small industrial and riverfront city in northeastern Kentucky, known as part of the Huntington–Ashland metropolitan area along the Ohio River.
-
D.
Ashland, Oregon
Ashland, Oregon is a small city in southern Oregon best known for its vibrant arts scene and the renowned Oregon Shakespeare Festival.
-
E.
Kelso
Kelso is a historic market town in the Scottish Borders, known for its picturesque setting at the confluence of the Rivers Tweed and Teviot and the ruins of Kelso Abbey.
- 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: Ashland Triple: [CTA Pink Line, hasStation, Ashland]
Generated description
Ashland is a Chicago 'L' rapid transit station on the CTA's Pink Line serving the city's Near West Side.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ashland Target entity description: Ashland is a Chicago 'L' rapid transit station on the CTA's Pink Line serving the city's Near West Side.
-
A.
Ashland
Ashland is an unincorporated community in Alameda County, California, situated in the East Bay region of the San Francisco Bay Area.
-
B.
Ashland, Ohio
Ashland, Ohio is a small city in north-central Ohio known historically as a regional manufacturing and agricultural center and home to Ashland University.
-
C.
Ashland, Kentucky
Ashland, Kentucky is a small industrial and riverfront city in northeastern Kentucky, known as part of the Huntington–Ashland metropolitan area along the Ohio River.
-
D.
Ashland, Oregon
Ashland, Oregon is a small city in southern Oregon best known for its vibrant arts scene and the renowned Oregon Shakespeare Festival.
-
E.
Kelso
Kelso is a historic market town in the Scottish Borders, known for its picturesque setting at the confluence of the Rivers Tweed and Teviot and the ruins of Kelso Abbey.
- 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_69ad85d8042081908af94a04c410dec0 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc19c71608190a87c98214321214c |
completed | March 8, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b40316ebdc819088eb21b7087fb7e7 |
completed | March 13, 2026, 12:29 p.m. |
| NEDg | Description generation | batch_69b406f095488190b4543fa8008fe86c |
completed | March 13, 2026, 12:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b408744dcc819081308b7182a40c88 |
completed | March 13, 2026, 12:52 p.m. |
Created at: March 8, 2026, 3:22 p.m.