Triple
T23898186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Turow |
E600962
|
entity |
| Predicate | hasPartInUniverse |
P15645
|
FINISHED |
| Object | Kindle County |
—
|
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: Kindle County | Statement: [Scott Turow, hasPartInUniverse, Kindle County]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartInUniverse Context triple: [Scott Turow, hasPartInUniverse, Kindle County]
-
A.
hasFictionalUniverseElement
chosen
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
B.
hasInUniverseInhabitants
Indicates that a universe or fictional setting contains certain beings or populations as its inhabitants.
-
C.
hasInUniverseLocationRelation
Indicates a relationship where an entity is associated with, or situated at, a specific location within a fictional or defined universe or setting.
-
D.
inUniverse
Indicates that one entity exists, occurs, or is set within the fictional or conceptual universe defined by another entity.
-
E.
hasFictionalUniverseProperty
Indicates that a fictional universe possesses a specific characteristic, attribute, or property.
- 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_69e295341ac0819080647f2908af793c |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cddb3fdc819096dc84a1774d9bee |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:25 p.m.