Triple
T13583386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zachary |
E324480
|
entity |
| Predicate | hasNickName |
P39
|
FINISHED |
| Object | Zac |
E91934
|
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: Zac | Statement: [Zachary, hasNickName, Zac]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zac Context triple: [Zachary, hasNickName, Zac]
-
A.
Zac
chosen
Zac is a common shortened form of the given name Isaac.
-
B.
Zack
Zack is a central character in Guy Ritchie's 2005 crime thriller film "Revolver," involved in the movie's intricate web of cons, psychological manipulation, and underworld dealings.
-
C.
Zach
Zach is a fictional character played by American actor Charlie Tahan, known for his roles in film and television.
-
D.
Zach
Zach is a lively, theatrical evacuee boy in the novel "Goodnight Mister Tom," known for his exuberant personality and close friendship with fellow evacuee Willie Beech.
-
E.
Zach
Zach is a common shortened form of the given name Zachary, often used as a casual or familiar nickname.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb031e8048190a5f2ea934308036c |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0d759fc81908c327850a4836ecd |
completed | May 3, 2026, 9:40 p.m. |
Created at: April 9, 2026, 9:49 p.m.