Triple
T17095060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Hughes |
E414824
|
entity |
| Predicate | hasRelationshipWith |
P2830
|
FINISHED |
| Object | John Dixon |
E1250074
|
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: John Dixon | Statement: [Kim Hughes, hasRelationshipWith, John Dixon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Dixon Context triple: [Kim Hughes, hasRelationshipWith, John Dixon]
-
A.
John Dixon
chosen
John Dixon is known primarily as the husband of former Australian Test cricket captain Kim Hughes.
-
B.
Frank Dixon
Frank Dixon is the strict and bureaucratic airport customs director in the film "The Terminal," who clashes with stranded traveler Viktor Navorski.
-
C.
John Dickson
John Dickson is a television and film composer best known for scoring the spy drama series "Burn Notice."
-
D.
Jackson Roykirk
Jackson Roykirk is a fictional scientist in the Star Trek universe known for designing the advanced space probe that later becomes the powerful entity Nomad.
-
E.
Frank Yates
Frank Yates was a prominent British statistician known for his influential work in experimental design and agricultural statistics.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbfc9158819081689d3d594a1908 |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139fbcbc08190be2a96d03daf0384 |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:35 a.m.