Triple
T13335736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joanna Leary |
E317686
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Leary |
E599774
|
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: Leary | Statement: [Joanna Leary, familyName, Leary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leary Context triple: [Joanna Leary, familyName, Leary]
-
A.
Leary
chosen
Leary is a surname of Irish origin that appears as a variant of the name O'Leary.
-
B.
Patrick "Lights" Leary
Patrick "Lights" Leary is the fictional former heavyweight boxing champion and family man at the center of the TV drama series "Lights Out."
-
C.
Timothy Leary
Timothy Leary was an American psychologist and writer best known for advocating the therapeutic and spiritual use of psychedelic drugs during the 1960s counterculture movement.
-
D.
Lyerly
Lyerly is a small town located in Chattooga County in the northwestern part of the U.S. state of Georgia.
-
E.
Dolores Haze
Dolores Haze is the fictional adolescent girl at the center of Vladimir Nabokov’s novel "Lolita," whose exploitation by the narrator drives the book’s controversial and tragic story.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d00b75c8190af98784c7df904c8 |
completed | April 11, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f39f298819088d79cda3ac2b375 |
completed | May 3, 2026, 10:11 a.m. |
Created at: April 9, 2026, 9:30 p.m.