Triple
T10130262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff MacNelly |
E226319
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jeff |
E162857
|
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: Jeff | Statement: [Jeff MacNelly, givenName, Jeff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Context triple: [Jeff MacNelly, givenName, Jeff]
-
A.
Jeff
chosen
Jeff is a masculine given name commonly used in English-speaking countries, often as a short form of Jeffrey or Jefferson.
-
B.
Jeff
Jeff is a supporting gangster character in the British crime film "The Long Good Friday," involved in the criminal underworld surrounding London mob boss Harold Shand.
-
C.
Jay
Jay is a small town located in Santa Rosa County in the northwestern part of Florida.
-
D.
Jay
Jay is a former American football placekicker and current sports commentator best known for his long NFL career and broadcasting work.
-
E.
Jay
Jay is the given first name of J. B. Pritzker, the American businessman, philanthropist, and governor of Illinois.
- 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_69ca843057b48190a86730167f5d6b98 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd33438988190be45878f98695816 |
completed | April 2, 2026, 2:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc7c50b08190a04aa2f58a6c300a |
completed | April 5, 2026, 8:56 p.m. |
Created at: March 30, 2026, 9:05 p.m.