Triple
T7298070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Browning |
E164573
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | John |
unclear NED1
|
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 Browning, hasGivenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Browning, hasGivenName, John]
-
A.
John
John is the husband of Martha Rainsborough.
-
B.
John
John is the first name of Pete Ricketts, an American businessman and politician who has served as governor of Nebraska.
-
C.
John
John IV of Portugal was a 17th-century Portuguese king who restored the country's independence from Spain and founded the Braganza dynasty.
-
D.
John
John is the given name of John Henry Patterson, an American industrialist and founder of the National Cash Register Company.
-
E.
John
John is the first name of J. Michael Luttig, a prominent American conservative jurist and former federal appellate judge.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8f83c881909e8eae85410f9659 |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81eb53060819081312e8b2805e9db |
completed | March 28, 2026, 6:32 p.m. |
Created at: March 27, 2026, 3 p.m.