Triple
T34239433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richmond railway station |
E878421
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object |
Richmond line
The Richmond line is a suburban railway line in Sydney, Australia, connecting the city’s western suburbs to Richmond and integrating with the broader Sydney Trains network.
|
E2087878
|
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: Richmond line | Statement: [Richmond railway station, servedByLine, Richmond line]
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: Richmond line Triple: [Richmond railway station, servedByLine, Richmond line]
Generated description
The Richmond line is a suburban railway line in Sydney, Australia, connecting the city’s western suburbs to Richmond and integrating with the broader Sydney Trains network.
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_69f349b22d8c819096b22df268382aa9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7127d3e30819094f2a86ca45ae307 |
completed | May 3, 2026, 9:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36d5e91e8c8190b714d5f40d25aa03 |
completed | June 20, 2026, 6:03 p.m. |
| NEDg | Description generation | batch_6a36d9b87fe08190bf7f461a1f88e0df |
completed | June 20, 2026, 6:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a36da1988908190a99638ba9a05097a |
completed | June 20, 2026, 6:21 p.m. |
Created at: May 1, 2026, 1:56 a.m.