Triple
T16672608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Sufferer & the Witness |
E405141
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Roadside |
E82522
|
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: Roadside | Statement: [The Sufferer & the Witness, hasPart, Roadside]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roadside Context triple: [The Sufferer & the Witness, hasPart, Roadside]
-
A.
Roadside
chosen
"Roadside" is a 1929 stage comedy by American playwright Lynn Riggs that humorously portrays life and romance in the rural American Southwest.
-
B.
Road
"Road" is a film featuring actor Ebon Moss-Bachrach in a significant role.
-
C.
Back Roads
Back Roads is a 2018 American drama-thriller film, based on Tawni O’Dell’s novel, in which Nicola Peltz Beckham plays a significant supporting role.
-
D.
Highway
"Highway" is a 2014 Indian Hindi-language road drama film directed by Imtiaz Ali, for which A. R. Rahman composed the acclaimed soundtrack.
-
E.
Highway
Highway is a 2002 American road drama film starring Jake Gyllenhaal and Jared Leto, following two friends on the run after a violent encounter in Las Vegas.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ca276848190b7562d7cb88d21e0 |
completed | April 18, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3916508190bd5edd91310ddb5a |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.