Triple
T23872554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oimachi Station |
E592765
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Oimachi commercial district
The Oimachi commercial district is a bustling shopping and entertainment area in Tokyo known for its mix of retail stores, restaurants, and local businesses that cater to commuters and residents around Oimachi Station.
|
E1619775
|
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: Oimachi commercial district | Statement: [Oimachi Station, locatedNear, Oimachi commercial district]
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: Oimachi commercial district Triple: [Oimachi Station, locatedNear, Oimachi commercial district]
Generated description
The Oimachi commercial district is a bustling shopping and entertainment area in Tokyo known for its mix of retail stores, restaurants, and local businesses that cater to commuters and residents around Oimachi Station.
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_69e25d23a5c88190ae3999c70ca15e08 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cbfed81881909905f71377f759b1 |
completed | April 29, 2026, 9:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0facf442d48190bd0185c7c6c6f268 |
completed | May 22, 2026, 1:10 a.m. |
| NEDg | Description generation | batch_6a0faedc316081908917e8bf3b7b3633 |
completed | May 22, 2026, 1:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0faf672b388190ab364df1ad746716 |
completed | May 22, 2026, 1:20 a.m. |
Created at: April 17, 2026, 8:14 p.m.