Triple
T629845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Williams |
E15901
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Williams
Williams is a common English surname borne by numerous notable figures across sports, politics, arts, and entertainment.
|
E81905
|
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: Williams | Statement: [Ted Williams, familyName, Williams]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Williams Context triple: [Ted Williams, familyName, Williams]
-
A.
Wilson
Wilson is a common English-language surname borne by numerous notable figures across fields such as science, politics, sports, and the arts.
-
B.
Wilson
Wilson is a Chicago Transit Authority 'L' station on the North Side that serves as a major stop on the Red Line.
-
C.
Johnson
Johnson is a common English surname borne by numerous notable individuals across politics, arts, sports, and other fields.
-
D.
Clinton
Clinton is a prominent American political surname most famously associated with Hillary Clinton, the former U.S. Secretary of State, senator, and First Lady.
-
E.
Clinton
Clinton is a small town in Dutchess County, New York, known for its rural character and historic Hudson Valley setting.
- 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: Williams Triple: [Ted Williams, familyName, Williams]
Generated description
Williams is a common English surname borne by numerous notable figures across sports, politics, arts, and entertainment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Williams Target entity description: Williams is a common English surname borne by numerous notable figures across sports, politics, arts, and entertainment.
-
A.
Wilson
Wilson is a Chicago Transit Authority 'L' station on the North Side that serves as a major stop on the Red Line.
-
B.
Wilson
Wilson is a common English-language surname borne by numerous notable figures across fields such as science, politics, sports, and the arts.
-
C.
Johnson
Johnson is a common English surname borne by numerous notable individuals across politics, arts, sports, and other fields.
-
D.
Clinton
Clinton is a prominent American political surname most famously associated with Hillary Clinton, the former U.S. Secretary of State, senator, and First Lady.
-
E.
Clinton
Clinton is a small town in Dutchess County, New York, known for its rural character and historic Hudson Valley setting.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ec051bc8190b3e3f8651a367d77 |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5914419848190bfdc565fb9a80022 |
completed | March 2, 2026, 1:31 p.m. |
| NEDg | Description generation | batch_69a5921e700081909ffd12d1186d4395 |
completed | March 2, 2026, 1:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5927bd8508190b390136092103835 |
completed | March 2, 2026, 1:37 p.m. |
Created at: March 1, 2026, 7:35 p.m.