Triple
T13251147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M1 line |
E315531
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Ulus station
Ulus station is a metro stop on the M1 line of the Ankara Metro system in Ankara, Turkey.
|
E1028579
|
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: Ulus station | Statement: [M1 line, hasStation, Ulus station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ulus station Context triple: [M1 line, hasStation, Ulus station]
-
A.
Limon Station
Limon Station was a railroad station whose presence and significance led to the nearby Colorado town of Limon being named in its honor.
-
B.
Juramento station
Juramento station is a stop on Buenos Aires’ Line D subway serving the Belgrano neighborhood.
-
C.
Fo Tan station
Fo Tan station is a Mass Transit Railway (MTR) station in the Sha Tin District of Hong Kong, serving the Fo Tan area on the East Rail line.
-
D.
Hamar Station
Hamar Station is a railway station in the town of Hamar in Innlandet county, Norway, serving as a regional transport hub on the country’s rail network.
-
E.
Lunner Station
Lunner Station is a local railway station in Lunner, Norway, serving regional passenger traffic on the Gjøvik Line.
- 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: Ulus station Triple: [M1 line, hasStation, Ulus station]
Generated description
Ulus station is a metro stop on the M1 line of the Ankara Metro system in Ankara, Turkey.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ulus station Target entity description: Ulus station is a metro stop on the M1 line of the Ankara Metro system in Ankara, Turkey.
-
A.
Limon Station
Limon Station was a railroad station whose presence and significance led to the nearby Colorado town of Limon being named in its honor.
-
B.
Juramento station
Juramento station is a stop on Buenos Aires’ Line D subway serving the Belgrano neighborhood.
-
C.
Fo Tan station
Fo Tan station is a Mass Transit Railway (MTR) station in the Sha Tin District of Hong Kong, serving the Fo Tan area on the East Rail line.
-
D.
Hamar Station
Hamar Station is a railway station in the town of Hamar in Innlandet county, Norway, serving as a regional transport hub on the country’s rail network.
-
E.
Lunner Station
Lunner Station is a local railway station in Lunner, Norway, serving regional passenger traffic on the Gjøvik Line.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f73423c8190932a9edac56df383 |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff393898819083bdf726466fcbe0 |
completed | May 3, 2026, 7:54 a.m. |
| NEDg | Description generation | batch_69f7013b3428819083c2bb6032aa08d4 |
completed | May 3, 2026, 8:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f702b40f088190bc3c24321309dfb1 |
completed | May 3, 2026, 8:09 a.m. |
Created at: April 9, 2026, 9:24 p.m.