Triple
T22767325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claire Standish |
E563160
|
entity |
| Predicate | settingTown |
P7747
|
FINISHED |
| Object | Shermer, Illinois |
—
|
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: Shermer, Illinois | Statement: [Claire Standish, settingTown, Shermer, Illinois]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingTown Context triple: [Claire Standish, settingTown, Shermer, Illinois]
-
A.
settingCity
chosen
Indicates that a work or event takes place in, or is primarily located within, a particular city.
-
B.
fromTown
Indicates that one entity originates from, or is associated as being from, a particular town represented by the other entity.
-
C.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
D.
mainSettlement
Indicates that one settlement serves as the primary or most important settlement associated with a given area, region, or administrative unit.
-
E.
primaryTown
Indicates that a given town is the main or most important town associated with an entity (such as a person, organization, or region).
- 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a81d3348190b005a43a5e03d406 |
completed | April 29, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69eed2b88d88819096015deb6a648801 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:27 p.m.