Triple
T36351223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Dad Was Nearly James Bond |
E895208
|
entity |
| Predicate | mainSubject |
P3
|
FINISHED |
| Object |
Des Bishop's father
Des Bishop's father is the central real-life figure portrayed in the comedian's autobiographical show and book "My Dad Was Nearly James Bond," which explores his near-miss with fame and his later battle with cancer.
|
E2180657
|
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: Des Bishop's father | Statement: [My Dad Was Nearly James Bond, mainSubject, Des Bishop's father]
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: Des Bishop's father Triple: [My Dad Was Nearly James Bond, mainSubject, Des Bishop's father]
Generated description
Des Bishop's father is the central real-life figure portrayed in the comedian's autobiographical show and book "My Dad Was Nearly James Bond," which explores his near-miss with fame and his later battle with cancer.
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_69f76e4f437c8190a1af3ea2564f41f5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7baa4e0f081909d30f14b8aa2a927 |
completed | May 3, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a39a329e2488190b39d42dd7112a793 |
completed | June 22, 2026, 9:03 p.m. |
| NEDg | Description generation | batch_6a39a4608b3481909ecc1119384ef337 |
completed | June 22, 2026, 9:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a39a599bce88190950bc55a2e74ea29 |
completed | June 22, 2026, 9:14 p.m. |
Created at: May 3, 2026, 4:09 p.m.