Triple
T18547871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pfc. Louden Downey |
E453284
|
entity |
| Predicate | legalStatusAtStartOfFilm |
P132103
|
FINISHED |
| Object | accused |
—
|
LITERAL 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: accused | Statement: [Pfc. Louden Downey, legalStatusAtStartOfFilm, accused]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusAtStartOfFilm Context triple: [Pfc. Louden Downey, legalStatusAtStartOfFilm, accused]
-
A.
statusAtStartOfFilm
Indicates the condition or situation an entity is in at the beginning of the film.
-
B.
legalStatusAtIssue
Indicates that the legal status of an entity is the central subject of dispute, consideration, or determination in a legal context.
-
C.
legalStatusAtDiscovery
Indicates the legal status or condition of an entity at the specific time it was discovered or first identified.
-
D.
legalStatusBefore
Indicates the legal condition or classification that applied to an entity prior to a specified event, change, or point in time.
-
E.
statusAtEndOfFilm
Indicates the condition or situation an entity is in when the film concludes.
- F. None of above. chosen
Provenance (4 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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e534be2298819095f637065fc2724e |
completed | April 19, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69e469e274a48190a570b25cfef4d890 |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2b93bc8190a6070018d7046547 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:38 a.m.