Triple
T9340221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dilios |
E224747
|
entity |
| Predicate | appearsIn |
P795
|
FINISHED |
| Object | 300 |
E44130
|
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: 300 | Statement: [Dilios, appearsIn, 300]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 300 Context triple: [Dilios, appearsIn, 300]
-
A.
300
chosen
300 is a 2006 stylized action film directed by Zack Snyder that dramatizes the Battle of Thermopylae through hyper-visual, graphic novel-inspired imagery.
-
B.
30
30 is Adele’s critically acclaimed third studio album, known for its soulful ballads and themes of heartbreak and self-reflection.
-
C.
300 (comic series)
300 (comic series) is a graphic novel by Frank Miller, with art by Lynn Varley, that stylizes and dramatizes the Battle of Thermopylae through bold visuals and mythic storytelling.
-
D.
The 305
The 305 is a nickname commonly used to refer to Miami, Florida, derived from its original area code.
-
E.
Mr. 3000
Mr. 3000 is a 2004 sports comedy film starring Bernie Mac as an arrogant former baseball star who must return to the game to reclaim his 3,000-hit milestone.
- 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_69ca84286fcc81909f6e7fd7a7e862a2 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4bae2e2481909effc2dc89a642c5 |
completed | April 1, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e3ed7ffc819090f3706a8be4cbfa |
completed | April 4, 2026, 10:11 a.m. |
Created at: March 30, 2026, 7:40 p.m.