Triple
T34339382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghost the Musical |
E881243
|
entity |
| Predicate | bookBasedOn |
P124205
|
FINISHED |
| Object | screenplay of Ghost (1990 film) |
—
|
LITERAL 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: screenplay of Ghost (1990 film) | Statement: [Ghost the Musical, bookBasedOn, screenplay of Ghost (1990 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookBasedOn Context triple: [Ghost the Musical, bookBasedOn, screenplay of Ghost (1990 film)]
-
A.
bookAdaptedInto
Indicates that a book has been turned into another work, typically in a different medium such as a film, TV series, or play.
-
B.
bookTieIn
chosen
Indicates that one creative work is directly related to another as a tie-in, typically produced to promote, expand, or accompany the original work (such as a book based on a film, game, or TV series).
-
C.
filmBasedOn
Indicates that a film is adapted from or derived from the story, characters, or events of another work.
-
D.
basedOnInFiction
Indicates that a fictional work, character, or element is derived from, inspired by, or modeled after another real or fictional source.
-
E.
filmBasedOnAuthor
Indicates that a film is based on works or writings created by a specific author.
- 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_69f349bc55e881908c8e338ef76b0043 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f717836f0c8190b4a397bbac37dd09 |
completed | May 3, 2026, 9:38 a.m. |
| PD | Predicate disambiguation | batch_69f7127a2ff08190b77d00963c9df621 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:58 a.m.