Triple
T2671711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brussels Metro |
E55760
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Stockel – Stokkel
Stockel – Stokkel is a metro station in the eastern part of Brussels serving as the terminus of line 1.
|
E288963
|
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: Stockel – Stokkel | Statement: [Brussels Metro, hasStation, Stockel – Stokkel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stockel – Stokkel Context triple: [Brussels Metro, hasStation, Stockel – Stokkel]
-
A.
Stod
Stod is a small town in the Plzeň Region of the Czech Republic that serves as a local administrative and service center for surrounding municipalities.
-
B.
Stabekk
Stabekk is a suburban area in Bærum, Norway, known for its residential neighborhoods, proximity to Oslo, and good transport connections.
-
C.
Stäket
Stäket is a locality in the northern Stockholm region of Sweden, situated within Järfälla Municipality and known for its residential areas and proximity to Lake Mälaren.
-
D.
Steenberg
Steenberg is a suburb in Cape Town, South Africa, situated near the Pollsmoor maximum-security prison.
-
E.
Stuckart
Stuckart is a German surname most notably associated with Wilhelm Stuckart, a high-ranking Nazi official and legal theorist involved in formulating racial laws during the Third Reich.
- 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: Stockel – Stokkel Triple: [Brussels Metro, hasStation, Stockel – Stokkel]
Generated description
Stockel – Stokkel is a metro station in the eastern part of Brussels serving as the terminus of line 1.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stockel – Stokkel Target entity description: Stockel – Stokkel is a metro station in the eastern part of Brussels serving as the terminus of line 1.
-
A.
Stod
Stod is a small town in the Plzeň Region of the Czech Republic that serves as a local administrative and service center for surrounding municipalities.
-
B.
Stabekk
Stabekk is a suburban area in Bærum, Norway, known for its residential neighborhoods, proximity to Oslo, and good transport connections.
-
C.
Stäket
Stäket is a locality in the northern Stockholm region of Sweden, situated within Järfälla Municipality and known for its residential areas and proximity to Lake Mälaren.
-
D.
Steenberg
Steenberg is a suburb in Cape Town, South Africa, situated near the Pollsmoor maximum-security prison.
-
E.
Stuckart
Stuckart is a German surname most notably associated with Wilhelm Stuckart, a high-ranking Nazi official and legal theorist involved in formulating racial laws during the Third Reich.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd98f98908190b5c6fb38d3d4367a |
completed | March 7, 2026, 7:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afa05f1ba48190a93a399d1067912c |
completed | March 10, 2026, 4:38 a.m. |
| NEDg | Description generation | batch_69afa180fadc8190b376687c8afb1748 |
completed | March 10, 2026, 4:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afa2172bc881908e17ab0eb3f9bb08 |
completed | March 10, 2026, 4:46 a.m. |
Created at: March 6, 2026, 9:54 p.m.