Triple
T38610639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Provincetown Players |
E934467
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
George Cram Cook
George Cram Cook was an American playwright and influential theater producer best known as a co-founder and driving force behind the experimental Provincetown Players, which helped launch modern American drama.
|
E2277929
|
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: George Cram Cook | Statement: [Provincetown Players, foundedBy, George Cram Cook]
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: George Cram Cook Triple: [Provincetown Players, foundedBy, George Cram Cook]
Generated description
George Cram Cook was an American playwright and influential theater producer best known as a co-founder and driving force behind the experimental Provincetown Players, which helped launch modern American drama.
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_69f76eccd6d081909ccce171011739a1 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcd97024448190a71051d4dfdd9457 |
completed | May 7, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41f4436a008190b2bd9922aa02d3a4 |
completed | June 29, 2026, 4:27 a.m. |
| NEDg | Description generation | batch_6a41f55d6f74819085b208204dcd68dc |
completed | June 29, 2026, 4:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41f61ba5a08190b74a5c3ec29c3665 |
completed | June 29, 2026, 4:35 a.m. |
Created at: May 3, 2026, 4:32 p.m.