Triple
T17165511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Crossing |
E416598
|
entity |
| Predicate | hasAccessPoint |
P1985
|
FINISHED |
| Object |
Poads Road
Poads Road is a rural access route commonly used as a starting point for reaching the Northern Crossing area.
|
E1738615
|
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: Poads Road | Statement: [Northern Crossing, hasAccessPoint, Poads Road]
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: Poads Road Triple: [Northern Crossing, hasAccessPoint, Poads Road]
Generated description
Poads Road is a rural access route commonly used as a starting point for reaching the Northern Crossing area.
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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f914a0748190b2658edbe576ea2d |
completed | April 18, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11fe39a89c81909f3a19e02ddb72ed |
completed | May 23, 2026, 7:21 p.m. |
| NEDg | Description generation | batch_6a11ff4907e88190aaad22b7390bc094 |
completed | May 23, 2026, 7:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a120048ef6c8190bf4467e0742a0421 |
completed | May 23, 2026, 7:30 p.m. |
Created at: April 10, 2026, 5:37 a.m.