Triple
T37721809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1941 Academy Awards |
E939603
|
entity |
| Predicate | precededBy |
P97
|
FINISHED |
| Object |
1940 Academy Awards
The 1940 Academy Awards ceremony honored the best films of 1939, including classics like "Gone with the Wind" and "The Wizard of Oz," and is remembered as one of Hollywood's most celebrated Oscar years.
|
E2240942
|
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: 1940 Academy Awards | Statement: [1941 Academy Awards, precededBy, 1940 Academy Awards]
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: 1940 Academy Awards Triple: [1941 Academy Awards, precededBy, 1940 Academy Awards]
Generated description
The 1940 Academy Awards ceremony honored the best films of 1939, including classics like "Gone with the Wind" and "The Wizard of Oz," and is remembered as one of Hollywood's most celebrated Oscar years.
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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbae7301e08190ac27ad92b33968bb |
completed | May 6, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40d67c10a08190910f828ce5008cac |
completed | June 28, 2026, 8:08 a.m. |
| NEDg | Description generation | batch_6a40d89fe3988190839b093c3559c73d |
completed | June 28, 2026, 8:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a40d9f174f481909c3c8adbe39ac518 |
completed | June 28, 2026, 8:23 a.m. |
Created at: May 3, 2026, 4:18 p.m.