Triple
T10286264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babes in Toyland (1961 film) |
E241235
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Kevin Corcoran |
E353300
|
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: Kevin Corcoran | Statement: [Babes in Toyland (1961 film), stars, Kevin Corcoran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kevin Corcoran Context triple: [Babes in Toyland (1961 film), stars, Kevin Corcoran]
-
A.
Kevin Corcoran
chosen
Kevin Corcoran was an American child actor best known for his roles in numerous Walt Disney films during the 1950s and 1960s.
-
B.
Kevin O'Connor
Kevin O'Connor is an American entrepreneur best known as the co-founder and former CEO of the online advertising company DoubleClick.
-
C.
Michael O’Rourke
Michael O’Rourke is an Irish media entrepreneur best known as a co-founder of the international sports television network Setanta Sports.
-
D.
Max Cullen
Max Cullen is an Australian character actor known for his extensive work in film, television, and theatre over several decades.
-
E.
Bill Quinn
Bill Quinn was an American character actor known for his numerous supporting roles in film and television from the 1930s through the 1980s.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b8343c819087c50e5471c46e3f |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e40205c8190a4788e1db1f149d2 |
completed | April 10, 2026, 4:36 a.m. |
Created at: April 6, 2026, 11:40 a.m.