Triple
T35531401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethan Montgomery |
E1026808
|
entity |
| Predicate | childhoodHomeLocation |
P27131
|
FINISHED |
| Object | rural Michigan |
—
|
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: rural Michigan | Statement: [Ethan Montgomery, childhoodHomeLocation, rural Michigan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: childhoodHomeLocation Context triple: [Ethan Montgomery, childhoodHomeLocation, rural Michigan]
-
A.
residenceOfChild
Indicates that a specified location is the place where a particular child lives or resides.
-
B.
placeOfUpbringing
chosen
Indicates the location where an individual was raised or spent most of their formative years.
-
C.
hasBoyhoodHomeOf
Indicates that a particular place served as the home where a male person lived during his childhood.
-
D.
homeLocationInStory
Indicates the place that serves as a character’s primary home or base of residence within the context of the story.
-
E.
homeCitySchool
Indicates that a particular city is the primary or designated home location associated with a given school.
- 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_69f76dff7e508190b28ceeee770dce23 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec355048190af30123ceb6efa2b |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:04 p.m.