Triple
T10771087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Ashton |
E254078
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | John |
E731271
|
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 | Statement: [John Ashton, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Ashton, givenName, John]
-
A.
John
John is the husband of Martha Rainsborough.
-
B.
John
John is the first name of J. Michael Luttig, a prominent American conservative jurist and former federal appellate judge.
-
C.
John
John J. McCloy was an influential American lawyer, banker, and statesman who served in key roles such as U.S. High Commissioner for Germany and president of the World Bank.
-
D.
John
chosen
John is the given name of John Howard, an Australian politician who served as the 25th Prime Minister of Australia.
-
E.
John
John is a fictional police detective and main character from the science fiction TV series "Almost Human."
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d732314bcc8190980c6f698f64ccf5 |
completed | April 9, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de55a12b8c8190bbeeb6d176f42b49 |
completed | April 14, 2026, 2:56 p.m. |
Created at: April 8, 2026, 9:16 p.m.