Triple
T36492119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ann Arbor Film Festival |
E899076
|
entity |
| Predicate | hasArtisticDirector |
P255
|
FINISHED |
| Object |
Leslie Raymond
Leslie Raymond is a film and media arts professional best known for serving as the artistic director of the Ann Arbor Film Festival, one of the oldest experimental film festivals in the United States.
|
E2185237
|
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: Leslie Raymond | Statement: [Ann Arbor Film Festival, hasArtisticDirector, Leslie Raymond]
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: Leslie Raymond Triple: [Ann Arbor Film Festival, hasArtisticDirector, Leslie Raymond]
Generated description
Leslie Raymond is a film and media arts professional best known for serving as the artistic director of the Ann Arbor Film Festival, one of the oldest experimental film festivals in the United States.
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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be27acbc81909ea7c1e26d49e019 |
completed | May 3, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a39cfe280988190a943c6305fa15bdc |
completed | June 23, 2026, 12:14 a.m. |
| NEDg | Description generation | batch_6a39d06ec8448190bce52dd9dcb925f4 |
completed | June 23, 2026, 12:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a39d12766ac8190a505dd6d49293937 |
completed | June 23, 2026, 12:19 a.m. |
Created at: May 3, 2026, 4:10 p.m.