Triple
T32899046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Minoes |
E841554
|
entity |
| Predicate | characterPlayedByTheoMaassen |
P199022
|
FINISHED |
| Object | Tibbe |
—
|
NE NERFINISHED |
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: Tibbe | Statement: [Miss Minoes, characterPlayedByTheoMaassen, Tibbe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedByTheoMaassen Context triple: [Miss Minoes, characterPlayedByTheoMaassen, Tibbe]
-
A.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
B.
characterPlayedByEdwardMulhare
Indicates that the subject is a character that was portrayed or played by Edward Mulhare.
-
C.
characterPlayedByNicholasHamilton
Indicates that the subject is a character portrayed by the actor Nicholas Hamilton.
-
D.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
E.
characterPlayedBy Emmanuelle Chriqui
Indicates that the role or character in question is portrayed or acted by Emmanuelle Chriqui.
- F. None of above. chosen
Provenance (4 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_69f34945ae408190b72d8118c83beb77 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff1ba8694481909ceb36f26ca85612 |
completed | May 9, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69ff1b27f0f08190a9e74308c5b3d1ba |
completed | May 9, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69ff1ba7494481908678a7a0f93dbd03 |
completed | May 9, 2026, 11:33 a.m. |
Created at: May 1, 2026, 1:19 a.m.