Triple
T16524965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Dover Grant |
E401410
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Die Trying |
E401412
|
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: Die Trying | Statement: [James Dover Grant, notableWork, Die Trying]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Die Trying Context triple: [James Dover Grant, notableWork, Die Trying]
-
A.
Die Trying
chosen
Die Trying is a thriller novel by Lee Child featuring ex-military drifter Jack Reacher as he becomes entangled in a violent kidnapping and conspiracy.
-
B.
“Die Trying”
“Die Trying” is a track by Cee-Lo Green featured on his debut solo album, Cee-Lo Green and His Perfect Imperfections, blending his distinctive soulful vocals with eclectic hip-hop and funk influences.
-
C.
Trikken
Trikken is the tram system serving Oslo, Norway, forming a key part of the city's public transportation network.
-
D.
Stößen
Stößen is a small town in the German state of Saxony-Anhalt that forms part of the broader Leipzig metropolitan area.
-
E.
Try and Stop Me
Try and Stop Me is a bestselling 1944 humor and anecdote collection by American publisher and writer Bennett Cerf.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed323c081908218460aa4ae3cf6 |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00608b7f6081909912dd575979f8d7 |
completed | May 10, 2026, 10:40 a.m. |
Created at: April 10, 2026, 5:14 a.m.