Triple
T15315635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William and Mary |
E366148
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Mick Ford |
E1091020
|
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: Mick Ford | Statement: [William and Mary, creator, Mick Ford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mick Ford Context triple: [William and Mary, creator, Mick Ford]
-
A.
Mick Ford
chosen
Mick Ford is a British screenwriter and actor known for adapting works such as "The Boy with the Topknot" for television.
-
B.
Mick Farmer
Mick Farmer is a notable individual distinguished enough in his field or public life to be recognized as a prominent bearer of the surname Farmer.
-
C.
Mick Ward
Mick Ward is a musician best known for his work with the band Kingfish.
-
D.
Mick Reid
Mick Reid is an alternative name used for the individual known as Mike Reid, likely referring to the same person in public or professional contexts.
-
E.
Mick Rogers
Mick Rogers is an Australian former professional road cyclist known for his time-trialling strength and multiple world championship titles in the team time trial.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dd1d384819098f38402a8740d91 |
completed | April 16, 2026, 1:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe60d4a08190833397c75b56932c |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 3:16 a.m.