Triple
T12127548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anam Campus |
E288846
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Anam Station |
E1544352
|
NE FINISHED |
How this triple was built (2 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: Anam Station | Statement: [Anam Campus, near, Anam Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anam Station Context triple: [Anam Campus, near, Anam Station]
-
A.
Anam Station
chosen
Anam Station is a subway station in Seoul, South Korea, serving the area around Korea University’s Anam Campus and nearby neighborhoods.
-
B.
Olema Station
Olema Station is the former name of the small coastal town now known as Point Reyes Station in Marin County, California.
-
C.
Onarimon Station
Onarimon Station is a Tokyo subway station on the Toei Mita Line located in Minato Ward, serving the business and park areas around Shiba and Tokyo Tower.
-
D.
Grua Station
Grua Station is a railway station serving the village of Grua in Lunner municipality in Viken county, Norway.
-
E.
Nopo Station
Nopo Station is a major subway and bus terminal in Busan, South Korea, serving as a key transportation hub for the northeastern part of the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9157ce6b88190b16592cc48244db3 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b4de0dec48190a74ccdef29499dfb |
completed | May 18, 2026, 5:35 p.m. |
Created at: April 8, 2026, 9:49 p.m.