Triple
T878471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justin Timberlake |
E18974
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Justin |
E42873
|
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: Justin | Statement: [Justin Timberlake, givenName, Justin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Justin Context triple: [Justin Timberlake, givenName, Justin]
-
A.
Justin
chosen
Justin is the given name of Justin Trudeau, the 23rd prime minister of Canada and leader of the Liberal Party.
-
B.
Jason
Jason is a famed hero of Greek mythology best known as the leader of the Argonauts in their quest for the Golden Fleece.
-
C.
Jason
Jason is the official mascot of the Canadian Football League’s Toronto Argonauts, typically depicted as a spirited, fan-engaging character representing the team.
-
D.
Jonathan
Jonathan is a common masculine given name of Hebrew origin, meaning "Yahweh has given."
-
E.
Jeremy
Jeremy is one of the central male protagonists in the romantic comedy film "Think Like a Man," which follows a group of men whose relationships are upended when their partners start using advice from Steve Harvey’s dating book.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acb1dc20819095b9bb093158b60d |
completed | March 1, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac11931dc88190ac1cd0d0c68a151d |
completed | March 7, 2026, 11:52 a.m. |
Created at: March 1, 2026, 7:39 p.m.