Triple
T18597336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aarhus Letbane |
E454525
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line L3
Line L3 is a light rail route that forms part of the Aarhus Letbane tram network in Aarhus, Denmark.
|
E1334786
|
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: Line L3 | Statement: [Aarhus Letbane, hasLine, Line L3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line L3 Context triple: [Aarhus Letbane, hasLine, Line L3]
-
A.
Line L2
Line L2 is one of the light rail routes of the Aarhus Letbane system in Aarhus, Denmark, providing urban and regional passenger transport.
-
B.
Line 3
Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
-
C.
Line 3
Line 3 is a Culver CityBus route in the Los Angeles area that connects key destinations across Culver City and nearby communities.
-
D.
Line 3
Line 3 is a metro line that intersects with Metro Line 9 within the same urban rail network, serving as one of its connecting routes.
-
E.
Line 3
Line 3 is a rapid transit line of the Hangzhou Metro system in Hangzhou, China, serving as part of the city's expanding urban rail network.
- 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: Line L3 Triple: [Aarhus Letbane, hasLine, Line L3]
Generated description
Line L3 is a light rail route that forms part of the Aarhus Letbane tram network in Aarhus, Denmark.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line L3 Target entity description: Line L3 is a light rail route that forms part of the Aarhus Letbane tram network in Aarhus, Denmark.
-
A.
Line L2
Line L2 is one of the light rail routes of the Aarhus Letbane system in Aarhus, Denmark, providing urban and regional passenger transport.
-
B.
Line 3
Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
-
C.
Line 3
Line 3 is a Culver CityBus route in the Los Angeles area that connects key destinations across Culver City and nearby communities.
-
D.
Line 3
Line 3 is a metro line that intersects with Metro Line 9 within the same urban rail network, serving as one of its connecting routes.
-
E.
Line 3
Line 3 is a rapid transit line of the Hangzhou Metro system in Hangzhou, China, serving as part of the city's expanding urban rail network.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5474ce0c08190b440cbe86b6ef7b9 |
completed | April 19, 2026, 9:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a050d6eb92c8190aa0c1f4eb0deb5cb |
completed | May 13, 2026, 11:46 p.m. |
| NEDg | Description generation | batch_6a050e04ebd881909120edb46168fbcb |
completed | May 13, 2026, 11:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a050e6112e88190a399cf58ea6c8401 |
completed | May 13, 2026, 11:50 p.m. |
Created at: April 10, 2026, 11:44 a.m.