Triple
T13648717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myra Breckinridge |
E326671
|
entity |
| Predicate | hasSequel |
P1961
|
FINISHED |
| Object | Myron |
E735037
|
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: Myron | Statement: [Myra Breckinridge, hasSequel, Myron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myron Context triple: [Myra Breckinridge, hasSequel, Myron]
-
A.
Myron
Myron is the birth name of American journalist and longtime 60 Minutes correspondent Mike Wallace.
-
B.
Myron
chosen
Myron is a fictional protagonist named in the work "The Hit," likely serving as the central figure driving the story’s action and conflict.
-
C.
Myron
Myron is a masculine given name of Greek origin, traditionally associated with the meaning “myrrh” or “fragrant oil.”
-
D.
Procles
Procles is a legendary descendant of Heracles and one of the twin founders of the Spartan royal dynasties in ancient Greek mythology.
-
E.
Cirón
Cirón is a river in southwestern France known for flowing through the Sauternes wine region, where its cool misty microclimate helps produce the area’s famous sweet wines.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc608466c81908f6d2c9c92cc86aa |
completed | April 12, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78afbf8948190ad38ea7529e52f16 |
completed | May 3, 2026, 5:50 p.m. |
Created at: April 9, 2026, 9:52 p.m.