Triple
T14358505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Ealy |
E356034
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Stumptown |
E768406
|
NE 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: Stumptown | Statement: [Michael Ealy, notableWork, Stumptown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stumptown Context triple: [Michael Ealy, notableWork, Stumptown]
-
A.
Stumptown
chosen
Stumptown is a television crime drama series based on the graphic novel of the same name, following a sharp-witted military veteran turned private investigator in Portland, Oregon.
-
B.
Stumptown
Stumptown is a historic nickname for Portland, Oregon, referencing the city’s rapid 19th-century growth that left tree stumps scattered throughout the area.
-
C.
L-Town
L-Town is a colloquial nickname for Lansing, the capital city of the U.S. state of Michigan.
-
D.
The Outfit
The Outfit is a 1973 American crime film, based on a Donald E. Westlake novel, that follows a professional thief seeking revenge against a powerful criminal syndicate.
-
E.
The Outfit
The Outfit is a 2022 crime thriller film centered on a meticulous English tailor in Chicago who becomes entangled with dangerous mobsters over the course of a tense night.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f52ca7881908704eef20228aed3 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c48dd408190ac45ad4ca6f610c3 |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 10, 2026, 1:15 a.m.