Triple
T19116935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul Subway Line 5 |
E467930
|
entity |
| Predicate | hasExtension |
P455
|
FINISHED |
| Object | Hanam Extension |
—
|
NE NERFINISHED |
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: Hanam Extension | Statement: [Seoul Subway Line 5, hasExtension, Hanam Extension]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanam Extension Context triple: [Seoul Subway Line 5, hasExtension, Hanam Extension]
-
A.
Hanam
chosen
Hanam is a city in South Korea known for its rapid urban development and large shopping and residential complexes, located just east of Seoul in Gyeonggi Province.
-
B.
Maihama
Maihama is a coastal district of Urayasu in Chiba Prefecture, Japan, best known as the location of the Tokyo Disney Resort.
-
C.
Haimoo
Haimoo is a small village located within the municipality of Vihti in southern Finland.
-
D.
Manan-gu
Manan-gu is a district-level administrative area within the city of Anyang in Gyeonggi Province, South Korea.
-
E.
Unami Park
Unami Park is a public recreational park located in Garwood, New Jersey, offering green space, sports facilities, and outdoor amenities for local residents.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e399a6d8819090a9501ff1637b9d |
completed | April 20, 2026, 8:28 a.m. |
Created at: April 10, 2026, 12:05 p.m.