Triple
T24070471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Judd Gray |
E596210
|
entity |
| Predicate | residenceAtTimeOfCrime |
P49534
|
FINISHED |
| Object | United States of America |
—
|
NE NERFINISHED |
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: United States of America | Statement: [Henry Judd Gray, residenceAtTimeOfCrime, United States of America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: residenceAtTimeOfCrime Context triple: [Henry Judd Gray, residenceAtTimeOfCrime, United States of America]
-
A.
residenceBeforeArrest
Indicates that a person lived at a particular residence prior to the time of their arrest.
-
B.
inResidenceAt
Indicates that an entity lives or resides at a particular location or residence.
-
C.
residenceDuringEvent
chosen
Indicates that an entity resides or is located at a particular place for the duration of a specified event.
-
D.
residenceBeforeImprisonment
Indicates the place where an individual lived prior to being imprisoned.
-
E.
residenceAtStartOfFilm
Indicates the place where a person or character is living at the beginning of the film.
- 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_69e288c25c008190850cf447940ab181 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1db17c99881909f97e858fb183d86 |
completed | April 29, 2026, 10:19 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:41 p.m.