Triple
T10916720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gavin Friday |
E257842
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hanvey |
E806031
|
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: Hanvey | Statement: [Gavin Friday, familyName, Hanvey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanvey Context triple: [Gavin Friday, familyName, Hanvey]
-
A.
Hanvey
chosen
Hanvey is a surname most notably associated with Scottish politician Neale Hanvey.
-
B.
Haydon
Haydon is the maiden surname of Vanessa Trump, who is known for her former marriage to Donald Trump Jr.
-
C.
Hadden
Hadden is a surname most notably associated with Briton Hadden, co-founder of Time magazine.
-
D.
Seitzenhahn
Seitzenhahn is a district of the town of Taunusstein in the Rheingau-Taunus region of Hesse, Germany.
-
E.
Vaughn
Vaughn is a surname most prominently associated with English film director and producer Matthew Vaughn, known for stylish action and comic-book adaptations.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7707deb608190903b1066e19600d3 |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e216fca9f48190b02e8c13b8f428bf |
completed | April 17, 2026, 11:18 a.m. |
Created at: April 8, 2026, 9:22 p.m.