Triple
T31838700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shadow of Hamlet |
E812740
|
entity |
| Predicate | drawsOnCharacter |
P15277
|
FINISHED |
| Object | Hamlet |
—
|
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: Hamlet | Statement: [Shadow of Hamlet, drawsOnCharacter, Hamlet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drawsOnCharacter Context triple: [Shadow of Hamlet, drawsOnCharacter, Hamlet]
-
A.
appliesToCharacter
Indicates that an action, rule, or property is specifically directed toward or relevant for a particular character.
-
B.
propertyOnCharacters
Indicates that a certain property or attribute is associated with one or more characters.
-
C.
screenCharacterBy
Indicates a relationship where one entity evaluates or selects characters according to certain criteria or standards.
-
D.
basedOnCharacterBy
chosen
Indicates that one work, adaptation, or portrayal is derived from or inspired by a character created by another entity.
-
E.
usedByCharacter
Indicates that something (such as an item, ability, or resource) is utilized or employed by a particular character.
- 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_69f348ea7ffc8190a2ab43d80277cf59 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b21e7e088190832a3db585daea1c |
completed | May 3, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 30, 2026, 11:48 p.m.