Triple
T30259589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great North Eastern Railway |
E769449
|
entity |
| Predicate | operatedRoute |
P18593
|
FINISHED |
| Object |
London King’s Cross to Sunderland
London King’s Cross to Sunderland is a long-distance intercity rail service in the United Kingdom linking the capital with the city of Sunderland in northeast England.
|
E1909985
|
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: London King’s Cross to Sunderland | Statement: [Great North Eastern Railway, operatedRoute, London King’s Cross to Sunderland]
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: London King’s Cross to Sunderland Triple: [Great North Eastern Railway, operatedRoute, London King’s Cross to Sunderland]
Generated description
London King’s Cross to Sunderland is a long-distance intercity rail service in the United Kingdom linking the capital with the city of Sunderland in northeast England.
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_69f22484a5f48190b678cd607700bc82 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f680a734788190ae3e75d06552d571 |
completed | May 2, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a277c0880948190a58dcb10a5779ae9 |
completed | June 9, 2026, 2:35 a.m. |
| NEDg | Description generation | batch_6a277d09f32c8190a75331cdfafd9456 |
completed | June 9, 2026, 2:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a277dc406308190a2e54214a8851a14 |
completed | June 9, 2026, 2:43 a.m. |
Created at: April 29, 2026, 7:41 p.m.