Triple
T24626283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Incheon SSG Landers Field |
E609548
|
entity |
| Predicate | publicTransitAccess |
P1288
|
FINISHED |
| Object |
Munhak Sports Complex Station
Munhak Sports Complex Station is a subway station in Incheon, South Korea, serving the Munhak Sports Complex area and nearby sports facilities.
|
E1739675
|
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: Munhak Sports Complex Station | Statement: [Incheon SSG Landers Field, publicTransitAccess, Munhak Sports Complex Station]
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: Munhak Sports Complex Station Triple: [Incheon SSG Landers Field, publicTransitAccess, Munhak Sports Complex Station]
Generated description
Munhak Sports Complex Station is a subway station in Incheon, South Korea, serving the Munhak Sports Complex area and nearby sports facilities.
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_69e2c4d1d3708190a0f2dc6a3a8523bb |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2aab63f0c8190a459eec33af403de |
completed | April 30, 2026, 1:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a12090c186c8190ace26c8afff630fa |
completed | May 23, 2026, 8:07 p.m. |
| NEDg | Description generation | batch_6a1209a175e481909f713b13a9e8d3a0 |
completed | May 23, 2026, 8:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a120a18cf84819084da110d13063fe9 |
completed | May 23, 2026, 8:12 p.m. |
Created at: April 18, 2026, 2:32 a.m.