Triple
T10143085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olive Ostrovsky |
E231633
|
entity |
| Predicate | interactsWith |
P3970
|
FINISHED |
| Object | Leaf Coneybear |
E211515
|
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: Leaf Coneybear | Statement: [Olive Ostrovsky, interactsWith, Leaf Coneybear]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leaf Coneybear Context triple: [Olive Ostrovsky, interactsWith, Leaf Coneybear]
-
A.
Leaf Coneybear
chosen
Leaf Coneybear is an eccentric, sweet-natured, and distractible homeschooled contestant in the musical "The 25th Annual Putnam County Spelling Bee," known for spelling words correctly while seemingly in a trance.
-
B.
Terry Cavanagh
Terry Cavanagh is an Irish musician best known as a member of the Celtic rock band O'Malley's March.
-
C.
Max Weiss
Max Weiss was a music industry figure best known as the founder of the influential jazz and blues label Fantasy Records.
-
D.
Weebo
Weebo is the quirky, floating robot assistant from Disney’s 1997 film "Flubber," known for its expressive personality and multimedia projections.
-
E.
Jared Keeso
Jared Keeso is a Canadian actor, writer, and producer best known for creating and starring in the comedy series "Letterkenny."
- 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_69ca848364f881908a24366a6feec1db |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdeb273fec8190818707167e031d58 |
completed | April 2, 2026, 4:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e618b0bc8190bc1d6f15dac2708e |
completed | April 5, 2026, 10:45 p.m. |
Created at: March 30, 2026, 9:07 p.m.