Triple
T4716963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John |
E104666
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Jan |
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: Jan | Statement: [John, hasVariant, Jan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jan Context triple: [John, hasVariant, Jan]
-
A.
Jan
Jan is the Dutch given name of Jan Peter Balkenende, the former Prime Minister of the Netherlands.
-
B.
Jan
Jan is an alternative romanization of the name Zhan, used to represent the same underlying name in different transliteration systems.
-
C.
Jan
Jan is a fictional character appearing in the Traveling Wilburys’ song “Tweeter and the Monkey Man,” which tells a noir-style crime story.
-
D.
Jan
Jan is the given name of the Dutch mathematician and philosopher Luitzen Egbertus Jan Brouwer, a founder of intuitionism in the foundations of mathematics.
-
E.
Jan
Jan is one of the central comic characters in Alan Ayckbourn’s stage play "Bedroom Farce," involved in the interwoven marital mishaps that drive the farcical plot.
- 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_69bd43ec4a348190bc41afae43375e71 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd640a32ec8190850146957885c3cf |
completed | March 20, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4d7f0bc88190b2e5a2d6cfd16892 |
completed | March 21, 2026, 7:49 a.m. |
Created at: March 20, 2026, 1:18 p.m.