Triple
T1913078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miskolc |
E38152
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object |
Asan
Asan is a city in South Korea known for its hot springs, historical sites, and growing role as an industrial and educational center.
|
E215809
|
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: Asan | Statement: [Miskolc, twinnedWith, Asan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asan Context triple: [Miskolc, twinnedWith, Asan]
-
A.
Akhasheni
Akhasheni is a Georgian red wine appellation from the Kakheti region, known for its naturally semi-sweet wines made primarily from Saperavi grapes.
-
B.
Sana'i
Sana'i was a pioneering 12th-century Persian Sufi poet whose mystical and didactic works profoundly shaped later poets, including Rumi.
-
C.
Askim
Askim is a town in southeastern Norway that serves as one of the locations for Østfold University College’s campuses.
-
D.
Atsi
Atsi is a regional dialect of the Fang language spoken by Fang communities in Central Africa.
-
E.
Asago
Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
- 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: Asan Triple: [Miskolc, twinnedWith, Asan]
Generated description
Asan is a city in South Korea known for its hot springs, historical sites, and growing role as an industrial and educational center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Asan Target entity description: Asan is a city in South Korea known for its hot springs, historical sites, and growing role as an industrial and educational center.
-
A.
Akhasheni
Akhasheni is a Georgian red wine appellation from the Kakheti region, known for its naturally semi-sweet wines made primarily from Saperavi grapes.
-
B.
Sana'i
Sana'i was a pioneering 12th-century Persian Sufi poet whose mystical and didactic works profoundly shaped later poets, including Rumi.
-
C.
Askim
Askim is a town in southeastern Norway that serves as one of the locations for Østfold University College’s campuses.
-
D.
Atsi
Atsi is a regional dialect of the Fang language spoken by Fang communities in Central Africa.
-
E.
Asago
Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
- 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_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1e26b948190aa194c30755ac5df |
completed | March 7, 2026, 5:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3d5972881908856b75b324a1ad2 |
completed | March 8, 2026, 10:10 p.m. |
| NEDg | Description generation | batch_69adf44290748190b882559de536af09 |
completed | March 8, 2026, 10:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adf4d0ac58819096659706ef0785d0 |
completed | March 8, 2026, 10:14 p.m. |
Created at: March 4, 2026, 7:35 p.m.