Triple
T1978687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pyeongtaek |
E42974
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object |
Osan
Osan is a city in Gyeonggi Province, South Korea, known for its proximity to Osan Air Base and its role as a regional transportation and commercial hub.
|
E223589
|
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: Osan | Statement: [Pyeongtaek, borderedBy, Osan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Osan Context triple: [Pyeongtaek, borderedBy, Osan]
-
A.
Osaka Evessa
Osaka Evessa is a professional Japanese basketball team based in Osaka that competes in the B.League.
-
B.
Asago
Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
-
C.
Tenjin
Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
-
D.
Nerima
Nerima is a residential ward in northwestern Tokyo known for its suburban character, parks, and role as a hub for anime production studios.
-
E.
Takatsuki
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
- 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: Osan Triple: [Pyeongtaek, borderedBy, Osan]
Generated description
Osan is a city in Gyeonggi Province, South Korea, known for its proximity to Osan Air Base and its role as a regional transportation and commercial hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Osan Target entity description: Osan is a city in Gyeonggi Province, South Korea, known for its proximity to Osan Air Base and its role as a regional transportation and commercial hub.
-
A.
Osaka Evessa
Osaka Evessa is a professional Japanese basketball team based in Osaka that competes in the B.League.
-
B.
Asago
Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
-
C.
Tenjin
Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
-
D.
Nerima
Nerima is a residential ward in northwestern Tokyo known for its suburban character, parks, and role as a hub for anime production studios.
-
E.
Takatsuki
Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb43011188190b6a41c004e9e4802 |
completed | March 7, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae032988ec8190b9012cbb77e7efa4 |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae03c4faac8190a13aa0882eda3629 |
completed | March 8, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0445a9608190918a7bd45b9bf999 |
completed | March 8, 2026, 11:20 p.m. |
Created at: March 4, 2026, 7:36 p.m.