Triple
T7299968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John |
E167820
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Jon |
E295174
|
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: Jon | Statement: [John, hasVariant, Jon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jon Context triple: [John, hasVariant, Jon]
-
A.
Jon
chosen
Jon is a masculine given name, often used as a shortened form or variant of names like Jonathan or John.
-
B.
Jo
Jo is a given name used across various cultures, often as a short form of names like Joseph, Joanna, or Jonathan.
-
C.
Josh
Josh is a fictional political operative best known as the sharp-witted Deputy White House Chief of Staff on the television series "The West Wing."
-
D.
Josh
Josh is a masculine given name commonly used in English-speaking countries, often as a short form of Joshua.
-
E.
Josh
Josh is a character in the horror film "Midsommar," portrayed as one of the American graduate students who travel to a remote Swedish commune for a midsummer festival that turns increasingly disturbing.
- 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_69c6888c820881909fc68f689fe1c251 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebaef4a081908fadc6d5e2621e80 |
completed | March 27, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e550645c819085effd46dff60f09 |
completed | March 28, 2026, 2:27 p.m. |
Created at: March 27, 2026, 3:01 p.m.