Triple
T2249659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie Howard |
E49586
|
entity |
| Predicate | deathPlaceContext |
P25017
|
FINISHED |
| Object | civilian airliner shot down during World War II |
—
|
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: civilian airliner shot down during World War II | Statement: [Leslie Howard, deathPlaceContext, civilian airliner shot down during World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathPlaceContext Context triple: [Leslie Howard, deathPlaceContext, civilian airliner shot down during World War II]
-
A.
placeOfDeath
Indicates the location where an entity (typically a person or animal) died.
-
B.
deathPlace_uncertain
Indicates that the place where an entity died is not known with certainty or is disputed.
-
C.
deathApprox
Indicates that an entity’s death occurred at an approximate, rather than exact, time or date.
-
D.
deathDescribedIn
chosen
Indicates that a person's death is documented, narrated, or otherwise detailed within a particular source or description.
-
E.
burialPlace
Indicates the location where a person or entity is buried.
- F. None of above.
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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0ef74988190a0af51d983cf5658 |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.