Triple
T8223785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roca Line |
E192127
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Glew
Glew is a town in the southern Greater Buenos Aires area of Argentina that serves as a stop on the Roca Line suburban railway network.
|
E719563
|
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: Glew | Statement: [Roca Line, hasStation, Glew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glew Context triple: [Roca Line, hasStation, Glew]
-
A.
Mesa 3D
Mesa 3D is an open-source implementation of the OpenGL and other graphics APIs that provides hardware-accelerated 3D rendering for Unix-like operating systems.
-
B.
OpenGL
OpenGL is a cross-language, cross-platform application programming interface (API) for rendering 2D and 3D vector graphics, widely used in games, simulations, and professional visualization.
-
C.
GLC
GLC is a Chicago-based rapper and longtime Kanye West collaborator known for his appearances on early Kanye albums and his affiliation with the G.O.O.D. Music collective.
-
D.
GLC
GLC is the National Rail station code for Glasgow Central, a major railway terminus in Glasgow, Scotland.
-
E.
GLC
GLC is a prominent and historic law college in Mumbai, India, officially known as Government Law College.
- 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: Glew Triple: [Roca Line, hasStation, Glew]
Generated description
Glew is a town in the southern Greater Buenos Aires area of Argentina that serves as a stop on the Roca Line suburban railway network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Glew Target entity description: Glew is a town in the southern Greater Buenos Aires area of Argentina that serves as a stop on the Roca Line suburban railway network.
-
A.
Mesa 3D
Mesa 3D is an open-source implementation of the OpenGL and other graphics APIs that provides hardware-accelerated 3D rendering for Unix-like operating systems.
-
B.
OpenGL
OpenGL is a cross-language, cross-platform application programming interface (API) for rendering 2D and 3D vector graphics, widely used in games, simulations, and professional visualization.
-
C.
GLC
GLC is a Chicago-based rapper and longtime Kanye West collaborator known for his appearances on early Kanye albums and his affiliation with the G.O.O.D. Music collective.
-
D.
GLC
GLC is the National Rail station code for Glasgow Central, a major railway terminus in Glasgow, Scotland.
-
E.
GLC
GLC is a prominent and historic law college in Mumbai, India, officially known as Government Law College.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb77cc351481908d7dcd6d3d15d59f |
completed | March 31, 2026, 7:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccee09ac548190a9988ff77d43e77e |
completed | April 1, 2026, 10:06 a.m. |
| NEDg | Description generation | batch_69ccf1bc720081908c4eabf58336318a |
completed | April 1, 2026, 10:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd05f26f9c8190a3cc00c03c6dda95 |
completed | April 1, 2026, 11:48 a.m. |
Created at: March 30, 2026, 5:45 p.m.