Triple
T4142549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kansas City, Kansas Public Schools |
E89303
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
USD 500
USD 500 is the unified school district serving Kansas City, Kansas, operating the public schools in that community.
|
E415108
|
NE FINISHED |
How this triple was built (4 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: USD 500 | Statement: [Kansas City, Kansas Public Schools, alsoKnownAs, USD 500]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: USD 500 Context triple: [Kansas City, Kansas Public Schools, alsoKnownAs, USD 500]
-
A.
Dollar
Dollar is a small historic town in Clackmannanshire, Scotland, known for its scenic setting near the Ochil Hills and the nearby Castle Campbell.
-
B.
Dollar
Dollar was a British pop duo, formed by David Van Day and Thereza Bazar, known for their catchy synth-pop hits in the late 1970s and early 1980s.
-
C.
Doller
The Doller is a river in northeastern France that flows through the Alsace region and joins the Ill near Mulhouse.
-
D.
USD
USD (Universal Scene Description) is an open-source 3D scene description and interchange framework developed by Pixar, widely used for creating, composing, and collaborating on complex virtual worlds and assets.
-
E.
USD
USD is a public research university located in Vermillion, South Dakota, known for its programs in law, medicine, and business.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: USD 500 Triple: [Kansas City, Kansas Public Schools, alsoKnownAs, USD 500]
Generated description
USD 500 is the unified school district serving Kansas City, Kansas, operating the public schools in that community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: USD 500 Target entity description: USD 500 is the unified school district serving Kansas City, Kansas, operating the public schools in that community.
-
A.
Dollar
Dollar is a small historic town in Clackmannanshire, Scotland, known for its scenic setting near the Ochil Hills and the nearby Castle Campbell.
-
B.
Dollar
Dollar was a British pop duo, formed by David Van Day and Thereza Bazar, known for their catchy synth-pop hits in the late 1970s and early 1980s.
-
C.
Doller
The Doller is a river in northeastern France that flows through the Alsace region and joins the Ill near Mulhouse.
-
D.
USD
USD (Universal Scene Description) is an open-source 3D scene description and interchange framework developed by Pixar, widely used for creating, composing, and collaborating on complex virtual worlds and assets.
-
E.
USD
USD is a public research university located in Vermillion, South Dakota, known for its programs in law, medicine, and business.
- F. None of above. chosen
Provenance (5 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af024cc7e88190b23b39d6f5f2a2e0 |
completed | March 9, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b576cff6c881909134804ba6f9876d |
completed | March 14, 2026, 2:55 p.m. |
| NEDg | Description generation | batch_69b577d391ac8190b6062b1f64e2e7e8 |
completed | March 14, 2026, 2:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5787ed214819092fc425152069df9 |
completed | March 14, 2026, 3:02 p.m. |
Created at: March 9, 2026, 3:43 p.m.