Triple
T32370630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunnery Sergeant Hartman |
E827123
|
entity |
| Predicate | deathSceneLocationInFiction |
P21
|
FINISHED |
| Object | recruit barracks bathroom |
—
|
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: recruit barracks bathroom | Statement: [Gunnery Sergeant Hartman, deathSceneLocationInFiction, recruit barracks bathroom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathSceneLocationInFiction Context triple: [Gunnery Sergeant Hartman, deathSceneLocationInFiction, recruit barracks bathroom]
-
A.
deathSceneFeature
Indicates that a particular feature, element, or characteristic is present in the scene depicting a character’s death.
-
B.
placeOfDeath
chosen
Indicates the location where an entity (typically a person or animal) died.
-
C.
traditionalPlaceOfDeath
Indicates the location where a person is customarily or culturally considered to have died, according to traditional or historical accounts.
-
D.
bodyLocationAfterDeath
Indicates the location or position of an entity’s body after its death.
-
E.
placeOfEvent_fakedDeath
Indicates the location where an event involving a faked or staged death took place.
- 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_69f349166d548190887b412fe908e2f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 12:50 a.m.