Triple
T10899798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeonpo-dong |
E257406
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object | Jeonpo Cafe Street |
E880381
|
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: Jeonpo Cafe Street | Statement: [Jeonpo-dong, hasNickname, Jeonpo Cafe Street]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeonpo Cafe Street Context triple: [Jeonpo-dong, hasNickname, Jeonpo Cafe Street]
-
A.
Munsu Street
Munsu Street is a major thoroughfare in Pyongyang, North Korea, known for hosting prominent political monuments and state landmarks.
-
B.
Seomyeon 1st Street
chosen
Seomyeon 1st Street is a popular shopping and entertainment district in Busan, South Korea, known for its dense concentration of shops, cafes, restaurants, and nightlife.
-
C.
Hang Bong Street
Hang Bong Street is a bustling historic street in Hanoi’s Old Quarter, known for its traditional shops, tailors, and textile stores.
-
D.
Gwangbok-dong shopping street
Gwangbok-dong shopping street is a popular commercial district in Busan, South Korea, known for its bustling pedestrian-friendly avenues lined with fashion boutiques, cafes, and local shops.
-
E.
Singil-dong
Singil-dong is a neighborhood (dong) in Seoul, South Korea, located within the city's southwestern Yeongdeungpo District.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d761a2392c8190bc2c2359d63eff7a |
completed | April 9, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e155306e9081909433522eeecf2b7d |
completed | April 16, 2026, 9:31 p.m. |
Created at: April 8, 2026, 9:21 p.m.