Triple
T9822314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The War You Don't See |
E238562
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Alan Lowery |
E238562
|
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: Alan Lowery | Statement: [The War You Don't See, producer, Alan Lowery]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alan Lowery Context triple: [The War You Don't See, producer, Alan Lowery]
-
A.
Alan Lowery
chosen
Alan Lowery is a film and television producer known for his work on the John Pilger documentary "The War You Don't See."
-
B.
Joe Lowry
Joe Lowry is a notable individual who shares the surname Lowry and has achieved sufficient recognition to be specifically distinguished among other bearers of the name.
-
C.
Pat Lowry
Pat Lowry is an individual notable enough to be recognized as a prominent bearer of the surname Lowry.
-
D.
Dan Harrow
Dan Harrow is the earnest, idealistic young farmer who serves as the central romantic lead in the stage musical and film "The Farmer Takes a Wife."
-
E.
Ian Meadows
Ian Meadows is an Australian actor and writer known for his work in television, film, and theatre.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb315ddf48190bd90f7835f409bb6 |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc7ce1908190a5131ef238541f0d |
completed | April 5, 2026, 2:44 a.m. |
Created at: March 30, 2026, 8:31 p.m.