Triple
T3664265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyber-King |
E77722
|
entity |
| Predicate | controlledBy |
P1715
|
FINISHED |
| Object | Miss Hartigan |
E378000
|
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: Miss Hartigan | Statement: [Cyber-King, controlledBy, Miss Hartigan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miss Hartigan Context triple: [Cyber-King, controlledBy, Miss Hartigan]
-
A.
Miss Hartigan
chosen
Miss Hartigan is a human antagonist from the Doctor Who universe who becomes partially converted by the Cybermen and serves as their primary human collaborator.
-
B.
Miss Marx
Miss Marx is a biographical drama film that portrays the life of Karl Marx’s youngest daughter, Eleanor Marx, focusing on her political activism and personal struggles.
-
C.
Margo
Margo is the responsible and intelligent eldest of Gru’s three adopted daughters in the Despicable Me franchise.
-
D.
Margo
Margo was a Mexican-American actress and dancer known for her work in Hollywood films of the 1930s and 1940s and for her later stage and television appearances.
-
E.
Miss Foster
Miss Foster is a fictional character from the musical play "Lady in the Dark," which explores psychoanalysis and a woman's inner emotional life.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3fe5eb08190ab15044acf9ac8a9 |
completed | March 8, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c39bb9b48190ba34226ccfccd59e |
completed | March 14, 2026, 2:10 a.m. |
Created at: March 8, 2026, 3:25 p.m.