Triple
T26115338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis Sachar |
E658807
|
entity |
| Predicate | hasWrittenSeries |
P42145
|
FINISHED |
| Object |
Wayside School series
The Wayside School series is a humorous children's book collection by Louis Sachar that follows the absurd and surreal adventures of students and teachers in a bizarre, thirty-story elementary school.
|
E1711251
|
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: Wayside School series | Statement: [Louis Sachar, hasWrittenSeries, Wayside School series]
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: Wayside School series Triple: [Louis Sachar, hasWrittenSeries, Wayside School series]
Generated description
The Wayside School series is a humorous children's book collection by Louis Sachar that follows the absurd and surreal adventures of students and teachers in a bizarre, thirty-story elementary school.
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_69ee5bc20298819099a42be042eb2349 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60ac72ad88190b27d7de5409b1d3f |
completed | May 2, 2026, 2:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11275455f481909068b62470d8885c |
completed | May 23, 2026, 4:04 a.m. |
| NEDg | Description generation | batch_6a112d28f9c08190bf93215c0d97cc23 |
completed | May 23, 2026, 4:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a112e27e4b08190be06432034aa7912 |
completed | May 23, 2026, 4:33 a.m. |
Created at: April 26, 2026, 8:04 p.m.