Triple
T10422685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Hinckley |
E245696
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hinckley |
E168604
|
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: Hinckley | Statement: [Thomas Hinckley, familyName, Hinckley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hinckley Context triple: [Thomas Hinckley, familyName, Hinckley]
-
A.
Hinckley
Hinckley is a small town in central Utah, United States, known for its rural agricultural setting and proximity to the Sevier Desert.
-
B.
Hinckley
chosen
Hinckley is a market town in southwest Leicestershire, England, known historically for its hosiery industry and its location between Coventry and Leicester.
-
C.
Mansfield
Mansfield is a small borough in northern Pennsylvania known for its rural setting and the presence of Mansfield University of Pennsylvania.
-
D.
Mansfield
Mansfield is a large market town in Nottinghamshire, England, known historically for its coal mining industry and proximity to Sherwood Forest.
-
E.
Mansfield
Mansfield is a suburban city in the Dallas–Fort Worth metropolitan area of North Texas, known for its residential communities, schools, and family-oriented amenities.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea2cd0788190b904ccdc251a9b7a |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fc2160208190b6384190d9537df4 |
completed | April 9, 2026, 7:21 p.m. |
Created at: April 6, 2026, 12:12 p.m.