Triple
T10567428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Shephard |
E249386
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ben |
E218629
|
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: Ben | Statement: [Ben Shephard, givenName, Ben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ben Context triple: [Ben Shephard, givenName, Ben]
-
A.
Ben
chosen
Ben is a common given name, typically used as a short form of names like Benedict or Benjamin.
-
B.
Bob
Bob is a common masculine given name, often used as a short form of Robert.
-
C.
Brian
Brian is a masculine given name of Irish origin that has become widely used in English-speaking countries.
-
D.
Joe
Joe is an American R&B singer and songwriter known for his smooth vocals and romantic ballads, particularly popular in the late 1990s and early 2000s.
-
E.
Joe
Joe is a central character in the classic 1959 comedy film "Some Like It Hot," where he is one of two musicians who disguise themselves as women to escape mobsters.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5272ef5848190b76d671ea2d26314 |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95e6e28a481909a90059e6ce51f6d |
completed | April 10, 2026, 8:32 p.m. |
Created at: April 6, 2026, 12:36 p.m.