Triple
T3715833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D Line |
E81527
|
entity |
| Predicate | servesArea |
P82
|
FINISHED |
| Object | Koreatown |
E315789
|
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: Koreatown | Statement: [D Line, servesArea, Koreatown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koreatown Context triple: [D Line, servesArea, Koreatown]
-
A.
Koreatown
Koreatown is a vibrant Manhattan neighborhood known for its dense concentration of Korean restaurants, shops, and cultural businesses centered around West 32nd Street near the Empire State Building.
-
B.
Koreatown
chosen
Koreatown is a dense Los Angeles neighborhood known for its vibrant Korean-American community, late-night dining, and mix of historic and modern urban development.
-
C.
Shin-Okubo Koreatown
Shin-Okubo Koreatown is a vibrant Korean cultural and commercial district in Tokyo known for its K-pop shops, Korean restaurants, and beauty stores.
-
D.
Gangnam District
Gangnam District is a wealthy, high-end commercial and residential area in Seoul, South Korea, known for its skyscrapers, luxury shopping, and vibrant nightlife.
-
E.
Itaewon
Itaewon is a vibrant multicultural district in Seoul known for its international cuisine, nightlife, and diverse expatriate community.
- 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc9cf77dc819098979094172d82d1 |
completed | March 8, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4ce0f690c819091d9caf9271f9bbd |
completed | March 14, 2026, 2:55 a.m. |
Created at: March 8, 2026, 3:33 p.m.