Triple
T32867601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carey Mulligan |
E840695
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Drive
Drive is a 2011 neo-noir action drama film known for its stylish direction, atmospheric synth soundtrack, and Ryan Gosling’s portrayal of a stoic Hollywood stunt driver who moonlights as a getaway driver.
|
E305552
|
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: Drive | Statement: [Carey Mulligan, notableWork, Drive]
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: Drive Triple: [Carey Mulligan, notableWork, Drive]
Generated description
Drive is a 2011 neo-noir action drama film known for its stylish direction, atmospheric synth soundtrack, and Ryan Gosling’s portrayal of a stoic Hollywood stunt driver who moonlights as a getaway driver.
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_69f34942465c819099b3fb47f9044f58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6cebc5ce48190a060af5a625126c2 |
completed | May 3, 2026, 4:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34bd1311188190835de335975311b8 |
completed | June 19, 2026, 3:52 a.m. |
| NEDg | Description generation | batch_6a34be2961548190996f1946ea749efe |
completed | June 19, 2026, 3:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a34bf150f8081909b249cb22230eb2e |
completed | June 19, 2026, 4:01 a.m. |
Created at: May 1, 2026, 1:17 a.m.