Triple
T15362500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Damen |
E367322
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object |
Robey
Robey is a former name of the Chicago Transit Authority’s Damen station, historically used for the stop on the city’s rapid transit system.
|
E1153711
|
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: Robey | Statement: [Damen, formerName, Robey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robey Context triple: [Damen, formerName, Robey]
-
A.
Robby
Robby is a common diminutive given name, typically used as a familiar or affectionate form of the name Robert.
-
B.
Reidy
Reidy is the surname of Affonso Eduardo Reidy, a prominent Brazilian modernist architect known for influential public housing and cultural projects in Rio de Janeiro.
-
C.
Roby
Roby is a suburban village and residential area within the Metropolitan Borough of Knowsley in Merseyside, England.
-
D.
Reeser
Reeser is a surname most notably associated with American actress Autumn Reeser, known for her roles in television and film.
-
E.
Ryen
Ryen is a residential neighborhood in Oslo, Norway, known for its apartment blocks, local amenities, and good public transport connections.
- 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: Robey Triple: [Damen, formerName, Robey]
Generated description
Robey is a former name of the Chicago Transit Authority’s Damen station, historically used for the stop on the city’s rapid transit system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Robey Target entity description: Robey is a former name of the Chicago Transit Authority’s Damen station, historically used for the stop on the city’s rapid transit system.
-
A.
Robby
Robby is a common diminutive given name, typically used as a familiar or affectionate form of the name Robert.
-
B.
Reidy
Reidy is the surname of Affonso Eduardo Reidy, a prominent Brazilian modernist architect known for influential public housing and cultural projects in Rio de Janeiro.
-
C.
Roby
Roby is a suburban village and residential area within the Metropolitan Borough of Knowsley in Merseyside, England.
-
D.
Reeser
Reeser is a surname most notably associated with American actress Autumn Reeser, known for her roles in television and film.
-
E.
Ryen
Ryen is a residential neighborhood in Oslo, Norway, known for its apartment blocks, local amenities, and good public transport connections.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e479f188190bbbc3dcd73853e02 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b4a181c8190bffc1ac1a86e215d |
completed | May 9, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69ff0f82441c81909a8ae13817fd3e96 |
completed | May 9, 2026, 10:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff0fd586708190a54b33efd27d84b2 |
completed | May 9, 2026, 10:43 a.m. |
Created at: April 10, 2026, 3:18 a.m.