Triple
T6821422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Little Prince |
E156906
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
the king
The king is a vain and authoritarian monarch whom the Little Prince meets on an asteroid, symbolizing adult obsession with power and control.
|
E621808
|
NE FINISHED |
How this triple was built (4 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: the king | Statement: [The Little Prince, hasCharacter, the king]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: the king Context triple: [The Little Prince, hasCharacter, the king]
-
A.
KING
KING is the stock ticker symbol for King Digital Entertainment, the video game company best known for creating the mobile puzzle game Candy Crush Saga.
-
B.
KING
KING is a television station in Seattle, Washington, known for its local news coverage and affiliation with major U.S. broadcast networks.
-
C.
Koning
Koning is a Dutch surname and term meaning “king,” commonly used in the Netherlands and Belgium.
-
D.
König
König is a German-language surname borne by numerous individuals, including notable figures in fields such as religion, science, and the arts.
-
E.
Kœnig
Kœnig is a French surname most notably associated with figures such as General Marie-Pierre Kœnig, a prominent military leader during World War II.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: the king Triple: [The Little Prince, hasCharacter, the king]
Generated description
The king is a vain and authoritarian monarch whom the Little Prince meets on an asteroid, symbolizing adult obsession with power and control.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: the king Target entity description: The king is a vain and authoritarian monarch whom the Little Prince meets on an asteroid, symbolizing adult obsession with power and control.
-
A.
KING
KING is the stock ticker symbol for King Digital Entertainment, the video game company best known for creating the mobile puzzle game Candy Crush Saga.
-
B.
KING
KING is a television station in Seattle, Washington, known for its local news coverage and affiliation with major U.S. broadcast networks.
-
C.
Koning
Koning is a Dutch surname and term meaning “king,” commonly used in the Netherlands and Belgium.
-
D.
König
König is a German-language surname borne by numerous individuals, including notable figures in fields such as religion, science, and the arts.
-
E.
Kœnig
Kœnig is a French surname most notably associated with figures such as General Marie-Pierre Kœnig, a prominent military leader during World War II.
- F. None of above. chosen
Provenance (5 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_69c688298a288190af3f285d57f76bbe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d35a8af08190a172c7baa16a3b62 |
completed | March 27, 2026, 6:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723eb23c8819085d2e8a8ce9c3c90 |
completed | March 28, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69c724b7b31081909c2bab4a3ba6e9f9 |
completed | March 28, 2026, 12:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c72536c4808190b9012e282cf02da4 |
completed | March 28, 2026, 12:47 a.m. |
Created at: March 27, 2026, 2:17 p.m.