Triple
T1714610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dark Tower series |
E37261
|
entity |
| Predicate | protagonist |
P268
|
FINISHED |
| Object | Roland Deschain |
E192778
|
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: Roland Deschain | Statement: [The Dark Tower series, protagonist, Roland Deschain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roland Deschain Context triple: [The Dark Tower series, protagonist, Roland Deschain]
-
A.
Roland Deschain
chosen
Roland Deschain is a stoic, relentless gunslinger on a quest to reach the Dark Tower in Stephen King’s epic fantasy series.
-
B.
Roland
Roland is a masculine given name of Germanic origin, historically associated with the legendary Frankish hero of "The Song of Roland" and later borne by various notable figures.
-
C.
Yorick Le Saux
Yorick Le Saux is a French cinematographer known for his visually striking, atmospheric work on art-house and independent films.
-
D.
Adelmorn the Outlaw
Adelmorn the Outlaw is a Gothic melodrama by Matthew Gregory Lewis, featuring a wronged hero turned outlaw amid dark, romantic intrigue.
-
E.
Auron
Auron is a river in central France that flows through the Cher department and joins the Yèvre near the city of Bourges.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa633349248190822e560fde817fc7 |
completed | March 6, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada0d3a1508190bf05aa45e9966c49 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 4, 2026, 7:30 p.m.