Triple
T3556901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTA Brown Line |
E75239
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
State/Lake
State/Lake is an elevated Chicago 'L' station in the Loop that serves the Brown Line and several other CTA train lines.
|
E366593
|
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: State/Lake | Statement: [CTA Brown Line, hasStation, State/Lake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: State/Lake Context triple: [CTA Brown Line, hasStation, State/Lake]
-
A.
Stan State
Stan State is the commonly used name for California State University, Stanislaus, a public university in Turlock, California, known for its diverse academic programs and regional impact.
-
B.
Aimeliik State
Aimeliik State is one of the states of Palau, located on the western side of the island of Babeldaob and known for its traditional villages and coastal mangrove forests.
-
C.
State
State is an underground subway station in downtown Boston that serves as a major transfer point between the MBTA Blue and Orange Lines.
-
D.
State
State is a behavioral design pattern that lets an object alter its behavior when its internal state changes, making it appear as if the object has changed its class.
-
E.
Iller
The Iller is a river in southern Germany that flows through Bavaria and Baden-Württemberg before joining the Danube.
- 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: State/Lake Triple: [CTA Brown Line, hasStation, State/Lake]
Generated description
State/Lake is an elevated Chicago 'L' station in the Loop that serves the Brown Line and several other CTA train lines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: State/Lake Target entity description: State/Lake is an elevated Chicago 'L' station in the Loop that serves the Brown Line and several other CTA train lines.
-
A.
Stan State
Stan State is the commonly used name for California State University, Stanislaus, a public university in Turlock, California, known for its diverse academic programs and regional impact.
-
B.
Aimeliik State
Aimeliik State is one of the states of Palau, located on the western side of the island of Babeldaob and known for its traditional villages and coastal mangrove forests.
-
C.
State
State is a behavioral design pattern that lets an object alter its behavior when its internal state changes, making it appear as if the object has changed its class.
-
D.
State
State is an underground subway station in downtown Boston that serves as a major transfer point between the MBTA Blue and Orange Lines.
-
E.
Iller
The Iller is a river in southern Germany that flows through Bavaria and Baden-Württemberg before joining the Danube.
- 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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc057cc788190a6c4f3781f43abce |
completed | March 8, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bf40dac8190837053dd315303af |
completed | March 13, 2026, 4 a.m. |
| NEDg | Description generation | batch_69b38c6e70a88190805de417a8740d64 |
completed | March 13, 2026, 4:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b38cd2c540819083d3188c2dea7283 |
completed | March 13, 2026, 4:04 a.m. |
Created at: March 8, 2026, 3:20 p.m.