Triple
T24502081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perimeter Center business district |
E617960
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
King and Queen Towers
King and Queen Towers are a pair of iconic twin high-rise office buildings in the Atlanta metropolitan area, recognizable for their distinctive crown-like tops and prominence in the local skyline.
|
E1639517
|
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: King and Queen Towers | Statement: [Perimeter Center business district, hasLandmark, King and Queen Towers]
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: King and Queen Towers Triple: [Perimeter Center business district, hasLandmark, King and Queen Towers]
Generated description
King and Queen Towers are a pair of iconic twin high-rise office buildings in the Atlanta metropolitan area, recognizable for their distinctive crown-like tops and prominence in the local skyline.
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_69e2d7f682108190a1a7ca5fd485ee8a |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a80277748190b34b174e9ec528eb |
completed | April 30, 2026, 12:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0fee874cd081908bfdc0bb7dc4d02c |
completed | May 22, 2026, 5:49 a.m. |
| NEDg | Description generation | batch_6a0fefe9541481909d7dbd79fdf1ef92 |
completed | May 22, 2026, 5:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ff0cc90508190b5d68bedeb4531aa |
completed | May 22, 2026, 5:59 a.m. |
Created at: April 18, 2026, 2:23 a.m.