Triple
T16674323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mummer |
E405179
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Wonderland
Wonderland is a fantastical, whimsical realm often depicted as a surreal and dreamlike setting in literature and popular culture.
|
E339877
|
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: Wonderland | Statement: [Mummer, hasPart, Wonderland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wonderland Context triple: [Mummer, hasPart, Wonderland]
-
A.
Wonderland
Wonderland is a rapid transit station in Revere, Massachusetts, serving as the northern terminus of Boston’s MBTA Blue Line.
-
B.
Wonderland
Wonderland is a song by the British pop group Take That, known for its upbeat, anthemic style and inclusion on their 2017 album of the same name.
-
C.
Wonderland
Wonderland is a 1999 British drama film directed by Michael Winterbottom that interweaves the lives of several Londoners over a Guy Fawkes Night weekend.
-
D.
Wonderland
Wonderland is a 1971 novel by Joyce Carol Oates that follows the psychologically intense and often disturbing life journey of a brilliant but traumatized man in American society.
-
E.
Wonderland
"Wonderland" is a dramatic work by Eric Bogosian that explores dark, contemporary themes through his signature intense, character-driven storytelling.
- 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: Wonderland Triple: [Mummer, hasPart, Wonderland]
Generated description
Wonderland is a fantastical, whimsical realm often depicted as a surreal and dreamlike setting in literature and popular culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wonderland Target entity description: Wonderland is a fantastical, whimsical realm often depicted as a surreal and dreamlike setting in literature and popular culture.
-
A.
Wonderland
chosen
Wonderland is a whimsical, surreal fantasy realm filled with peculiar characters and illogical rules, famously explored by Alice in Lewis Carroll’s classic stories and their adaptations.
-
B.
Wonderland
Wonderland is a 1971 novel by Joyce Carol Oates that follows the psychologically intense and often disturbing life journey of a brilliant but traumatized man in American society.
-
C.
Wonderland
Wonderland is a rapid transit station in Revere, Massachusetts, serving as the northern terminus of Boston’s MBTA Blue Line.
-
D.
Wonderland
Wonderland is a song by the British pop group Take That, known for its upbeat, anthemic style and inclusion on their 2017 album of the same name.
-
E.
Wonderland
Wonderland is a 1999 British drama film directed by Michael Winterbottom that interweaves the lives of several Londoners over a Guy Fawkes Night weekend.
- F. None of above.
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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6904008190a79ab30b6d9ccae9 |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3ab8b481908b333b6a556a58d5 |
completed | May 10, 2026, 1:38 p.m. |
| NEDg | Description generation | batch_6a008ad087b08190b725382c68687a15 |
completed | May 10, 2026, 1:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a008ba8227881908b1ac6e30d2e7c32 |
completed | May 10, 2026, 1:44 p.m. |
Created at: April 10, 2026, 5:19 a.m.