Triple
T28938025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keisei Main Line (airport access branch) |
E730369
|
entity |
| Predicate | usesRollingStock |
P5426
|
FINISHED |
| Object |
Keisei 3400 series EMU
The Keisei 3400 series EMU is a Japanese electric multiple unit train type operated by Keisei Electric Railway, primarily used for commuter and airport access services in the Tokyo–Narita corridor.
|
E1880694
|
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: Keisei 3400 series EMU | Statement: [Keisei Main Line (airport access branch), usesRollingStock, Keisei 3400 series EMU]
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: Keisei 3400 series EMU Triple: [Keisei Main Line (airport access branch), usesRollingStock, Keisei 3400 series EMU]
Generated description
The Keisei 3400 series EMU is a Japanese electric multiple unit train type operated by Keisei Electric Railway, primarily used for commuter and airport access services in the Tokyo–Narita corridor.
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_69f043ea0aa88190a25acbf46157995a |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65b809be4819081a3ae8def7bbdc1 |
completed | May 2, 2026, 8:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a26aa4db9b481909a60fb1e86f36253 |
completed | June 8, 2026, 11:41 a.m. |
| NEDg | Description generation | batch_6a26b54856b881909387662ffb868cd5 |
completed | June 8, 2026, 12:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a26b5a18df88190850a6c4c677b6564 |
completed | June 8, 2026, 12:29 p.m. |
Created at: April 28, 2026, 8:34 a.m.