Triple
T27937498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Hanks (narrator / older Hero Boy) |
E700651
|
entity |
| Predicate | appearsInBasedOn |
P795
|
FINISHED |
| Object | The Polar Express (1985 book) |
—
|
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: The Polar Express (1985 book) | Statement: [Tom Hanks (narrator / older Hero Boy), appearsInBasedOn, The Polar Express (1985 book)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInBasedOn Context triple: [Tom Hanks (narrator / older Hero Boy), appearsInBasedOn, The Polar Express (1985 book)]
-
A.
appearsIn
chosen
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
B.
appearsFor
Indicates that one entity is presented, shown, or made visible on behalf of, or in representation of, another entity.
-
C.
mayAppearOn
Indicates that one entity is allowed or able to be shown, featured, or present on another entity (such as a platform, medium, or surface).
-
D.
appearsAgainst
Indicates that one entity is visually or publicly presented in opposition to, or in contrast with, another entity.
-
E.
alsoAppearsAs
Indicates that an entity is known or presented under an alternative name, form, or representation.
- 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_69ef6a5028108190a14696d9821dde49 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 27, 2026, 7:14 p.m.