Triple
T3107516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Nickell |
E64867
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Joe |
E64867
|
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: Joe | Statement: [Joe Nickell, hasGivenName, Joe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Context triple: [Joe Nickell, hasGivenName, Joe]
-
A.
Joe
Joe is the given name of Joe Rosenthal, the American photographer famous for his iconic World War II image of the flag raising on Iwo Jima.
-
B.
Joe
chosen
Joe is the given name of Joe Nickell, an American investigator and author known for his work examining alleged paranormal and mysterious phenomena.
-
C.
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.
-
D.
Joe
Joe is a common masculine given name, often a short form of Joseph, used widely in English-speaking countries.
-
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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada29d4aa8819093287bc71370fc05 |
completed | March 8, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235a3ebac8190af9a25eeee778675 |
completed | March 12, 2026, 3:40 a.m. |
Created at: March 8, 2026, 3:04 p.m.