Triple
T28212797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip |
E711219
|
entity |
| Predicate | isCharacterInWorkSetIn |
P78408
|
FINISHED |
| Object | Melbourne |
—
|
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: Melbourne | Statement: [Philip, isCharacterInWorkSetIn, Melbourne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCharacterInWorkSetIn Context triple: [Philip, isCharacterInWorkSetIn, Melbourne]
-
A.
appearsInWorkSetIn
Indicates that an entity appears in a creative work whose narrative or setting takes place in a specified location or context.
-
B.
usedInWorkSetIn
Indicates that something (such as an element, motif, or device) is employed within a creative work whose narrative or content is set in a particular place or time.
-
C.
isCharacterInWorkLanguage
Indicates that a character appears in a work (e.g., book, film, game) in a specific language version or localization.
-
D.
hasWorkInCollection
Indicates that a work or item is included as part of a particular collection.
-
E.
isCharacterInSetting
chosen
Indicates that a particular character appears or exists within a specified setting or environment.
- F. None of above.
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_69efb51cb5288190818c1f63a266af11 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6434ad2248190a431a5a12c4123d2 |
completed | May 2, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 10:40 p.m.