Triple
T25342638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parsley Hay |
E635456
|
entity |
| Predicate | hasNearbyAttraction |
P2064
|
FINISHED |
| Object |
Arbor Low stone circle
Arbor Low stone circle is a major Neolithic henge monument in the Peak District of England, known for its impressive ring of recumbent stones and surrounding earthworks.
|
E1674338
|
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: Arbor Low stone circle | Statement: [Parsley Hay, hasNearbyAttraction, Arbor Low stone circle]
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: Arbor Low stone circle Triple: [Parsley Hay, hasNearbyAttraction, Arbor Low stone circle]
Generated description
Arbor Low stone circle is a major Neolithic henge monument in the Peak District of England, known for its impressive ring of recumbent stones and surrounding earthworks.
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_69e75a99bd6481909476115b35b9a8e4 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f498b936f08190b750199798e9effc |
completed | May 1, 2026, 12:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1075f6ffc081908a4d3175f79ef816 |
completed | May 22, 2026, 3:27 p.m. |
| NEDg | Description generation | batch_6a1076d69a948190a72c4e681021150c |
completed | May 22, 2026, 3:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a10776edaf8819086cfe23f2dea8a29 |
completed | May 22, 2026, 3:34 p.m. |
Created at: April 21, 2026, 1:32 p.m.