Triple
T17232215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Wildhorn |
E418269
|
entity |
| Predicate | wroteMusicFor |
P30214
|
FINISHED |
| Object | Wonderland |
E1256991
|
NE FINISHED |
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: Wonderland | Statement: [Frank Wildhorn, wroteMusicFor, Wonderland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wonderland Context triple: [Frank Wildhorn, wroteMusicFor, Wonderland]
-
A.
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.
-
B.
Wonderland
"Wonderland" is a dramatic work by Eric Bogosian that explores dark, contemporary themes through his signature intense, character-driven storytelling.
-
C.
Wonderland
chosen
Wonderland is a Broadway musical by composer Frank Wildhorn that offers a modern, pop-infused reimagining of Lewis Carroll’s Alice in Wonderland.
-
D.
Wonderland
Wonderland is a rapid transit station in Revere, Massachusetts, serving as the northern terminus of Boston’s MBTA Blue Line.
-
E.
Wonderland
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42df7da748190a3a1762a67eb871b |
completed | April 19, 2026, 1:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170ef3110819097ac1346ae33ef94 |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:39 a.m.