Triple
T5913971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Pie |
E131532
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Chris Moore |
E298746
|
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: Chris Moore | Statement: [American Pie, producer, Chris Moore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Moore Context triple: [American Pie, producer, Chris Moore]
-
A.
Chris Moore
chosen
Chris Moore is an American film producer known for his work on acclaimed independent films, including the Oscar-winning drama "Manchester by the Sea."
-
B.
Nick Moore
Nick Moore is a British film editor best known for his work on popular films such as "Love Actually."
-
C.
Rich Moore
Rich Moore is an American animation director and filmmaker best known for his work on acclaimed Disney films such as "Zootopia" and "Wreck-It Ralph."
-
D.
Tim Moore
Tim Moore is a film producer best known for his frequent collaborations with director Clint Eastwood on movies such as "Sully," "American Sniper," and "Gran Torino."
-
E.
Scott Moore
Scott Moore is an American screenwriter best known for co-writing the hit comedy film "The Hangover."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008593a44819081a07ae0efe6c574 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c037b9f0908190ad854e5f2600f114 |
completed | March 22, 2026, 6:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1134e27388190ad90faed28d2d360 |
completed | March 23, 2026, 10:17 a.m. |
Created at: March 22, 2026, 3:59 p.m.