Triple
T18262256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thea Kronborg |
E437386
|
entity |
| Predicate | growsUpIn |
P7868
|
FINISHED |
| Object | small town in Colorado |
—
|
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: small town in Colorado | Statement: [Thea Kronborg, growsUpIn, small town in Colorado]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: growsUpIn Context triple: [Thea Kronborg, growsUpIn, small town in Colorado]
-
A.
placeOfUpbringing
Indicates the location where an individual was raised or spent most of their formative years.
-
B.
growsIn
Indicates that one entity develops, thrives, or increases in size or number within a specified environment, medium, or location.
-
C.
growsFrom
Indicates that one entity develops, originates, or emerges from another as its source or substrate.
-
D.
raisedIn
chosen
Indicates that an entity spent its formative or upbringing period within a particular place or environment.
-
E.
sonRaisedIn
Indicates that a son spent his childhood or formative years being brought up in a particular place or environment.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff76a1208190abbe6ab8720ed154 |
completed | April 19, 2026, 4:14 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:34 a.m.