Triple
T2555304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SharePoint Framework |
E56717
|
entity |
| Predicate | uses |
P98
|
FINISHED |
| Object |
Yeoman
Yeoman is a scaffolding tool for modern web applications that streamlines project setup by generating boilerplate code and configuration through customizable generators.
|
E276983
|
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: Yeoman | Statement: [SharePoint Framework, uses, Yeoman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yeoman Context triple: [SharePoint Framework, uses, Yeoman]
-
A.
Yeomen and Yeowomen
Yeomen and Yeowomen are the athletic teams and mascots representing Oberlin College in intercollegiate sports.
-
B.
York Yeomen
York Yeomen was the former name of the varsity athletic teams representing York University in Toronto, Canada, before they were rebranded as the York Lions.
-
C.
Weaver
Weaver is a common English occupational surname historically given to people who worked as weavers of cloth or textiles.
-
D.
Hoyte
Hoyte is the first name of Hoyte van Hoytema, a renowned Dutch-Swedish cinematographer known for his work on major films such as "Interstellar" and "Dunkirk."
-
E.
Sergeant Putnam
Sergeant Putnam is a fictional military character played by British actor Bernard Hill.
- 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: Yeoman Triple: [SharePoint Framework, uses, Yeoman]
Generated description
Yeoman is a scaffolding tool for modern web applications that streamlines project setup by generating boilerplate code and configuration through customizable generators.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yeoman Target entity description: Yeoman is a scaffolding tool for modern web applications that streamlines project setup by generating boilerplate code and configuration through customizable generators.
-
A.
Yeomen and Yeowomen
Yeomen and Yeowomen are the athletic teams and mascots representing Oberlin College in intercollegiate sports.
-
B.
York Yeomen
York Yeomen was the former name of the varsity athletic teams representing York University in Toronto, Canada, before they were rebranded as the York Lions.
-
C.
Weaver
Weaver is a common English occupational surname historically given to people who worked as weavers of cloth or textiles.
-
D.
Hoyte
Hoyte is the first name of Hoyte van Hoytema, a renowned Dutch-Swedish cinematographer known for his work on major films such as "Interstellar" and "Dunkirk."
-
E.
Sergeant Putnam
Sergeant Putnam is a fictional military character played by British actor Bernard Hill.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd30eec988190810346bb8b6cb489 |
completed | March 7, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5d1ad6b4819097f1d18a12aa2b89 |
completed | March 9, 2026, 11:51 p.m. |
| NEDg | Description generation | batch_69af5dea244c81909bd6bcdba0edf958 |
completed | March 9, 2026, 11:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69af5e66a39c81909a49c272cd595c84 |
completed | March 9, 2026, 11:57 p.m. |
Created at: March 6, 2026, 9:48 p.m.