Triple
T10300495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seamus McGarvey |
E241614
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The War Zone (film) |
E199767
|
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: The War Zone (film) | Statement: [Seamus McGarvey, notableWork, The War Zone (film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The War Zone (film) Context triple: [Seamus McGarvey, notableWork, The War Zone (film)]
-
A.
The War Zone
chosen
The War Zone is a 1999 British drama film, adapted from Alexander Stuart’s novel, that starkly explores familial abuse and trauma.
-
B.
Forbidden Zone
Forbidden Zone is a 1980 cult musical fantasy film known for its surreal, low-budget style and early involvement of the band Oingo Boingo.
-
C.
5 Days of War
5 Days of War is a 2011 action-war film depicting the 2008 Russo-Georgian conflict through the perspective of an American journalist.
-
D.
Red Dawn
Red Dawn is a 1984 American war film depicting a group of small-town teenagers who form a guerrilla resistance after a Soviet-led invasion of the United States.
-
E.
Lord of War
Lord of War is a 2005 crime drama film following an international arms dealer as he navigates the global weapons trade and its moral consequences.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2eefe8881908a672c4dca7657ca |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d3f2c2c8190a71e4a896d8753e7 |
completed | April 9, 2026, 3:30 a.m. |
Created at: April 6, 2026, 11:44 a.m.