Triple
T5203763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Yates |
E117458
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Yates |
E247726
|
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: Yates | Statement: [David Yates, familyName, Yates]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yates Context triple: [David Yates, familyName, Yates]
-
A.
Yates
chosen
Yates is a surname of English origin borne by various notable individuals across literature, politics, sports, and other fields.
-
B.
Heseltine
Heseltine is a surname most prominently associated with Michael Heseltine, a senior British Conservative politician and former Deputy Prime Minister.
-
C.
Titsey
Titsey is a small rural village and civil parish in Surrey, England, known for its historic estate and scenic countryside near the North Downs.
-
D.
Sandys
Sandys is the surname of Frederic Sandys, a 19th-century British painter and illustrator associated with the Pre-Raphaelite movement.
-
E.
Tesseney
Tesseney is a town in western Eritrea near the Sudanese border, serving as a local commercial and agricultural center in the Gash-Barka region.
- 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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a46393c81908da08f4fbfb6147d |
completed | March 20, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee0a8ae0881909ce3173b73c2b749 |
completed | March 21, 2026, 6:17 p.m. |
Created at: March 20, 2026, 1:47 p.m.