Triple
T14472920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janiece |
E358889
|
entity |
| Predicate | isRelatedTo |
P37
|
FINISHED |
| Object | Janis |
E358888
|
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: Janis | Statement: [Janiece, isRelatedTo, Janis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Janis Context triple: [Janiece, isRelatedTo, Janis]
-
A.
Janis
chosen
Janis is a given name, often used as a variant of Janice, that can be masculine or feminine depending on cultural context.
-
B.
Janis Ian
Janis Ian is a sharp-witted, artsy outsider and key protagonist in the teen comedy film "Mean Girls," known for orchestrating a plan to take down the school's popular clique.
-
C.
Emily Ruth May
Emily Ruth May is a daughter of Queen guitarist and astrophysicist Brian May.
-
D.
Joni
Joni is a thoughtful, college-bound teenage daughter in the film "The Kids Are All Right," whose curiosity about her sperm-donor father helps drive the story’s family drama.
-
E.
Joni James
Joni James was an American traditional pop singer of the 1950s and 1960s known for her smooth, romantic vocal style and a string of chart-topping hits.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91fab21c819090b6e209d8efba6e |
completed | April 14, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd649e103c81908001b45c16d1fd79 |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 10, 2026, 1:20 a.m.