Triple
T2179071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Bolger |
E48998
|
entity |
| Predicate | role |
P268
|
FINISHED |
| Object | Scarecrow |
E48999
|
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: Scarecrow | Statement: [Ray Bolger, role, Scarecrow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scarecrow Context triple: [Ray Bolger, role, Scarecrow]
-
A.
Scarecrow
Scarecrow is a Batman supervillain and deranged psychiatrist who uses fear-inducing toxins to terrorize Gotham City.
-
B.
The Scarecrow
chosen
The Scarecrow is a beloved fictional figure from L. Frank Baum’s Oz stories, known for his quest for a brain and his role as one of Dorothy’s loyal companions.
-
C.
The Bat
The Bat is a popular inverted boomerang-style roller coaster at Canada's Wonderland known for its intense forward and backward loops.
-
D.
Robin
Robin is a given name commonly used in various cultures, often as a diminutive or variant of names like Robert.
-
E.
Boo
Boo is the young human girl in Pixar's animated film "Monsters, Inc." whose unexpected arrival in the monster world drives the story's central conflict and emotional core.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbeefb7648190b8fc57cf60553579 |
completed | March 7, 2026, 6 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71b142208190a09c8e459b200ecb |
completed | March 9, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:45 p.m.