Triple
T34934989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Train Trip |
E1007542
|
entity |
| Predicate | characterTypeOfNickAdams |
P60013
|
FINISHED |
| Object | recurring character |
—
|
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: recurring character | Statement: [A Train Trip, characterTypeOfNickAdams, recurring character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterTypeOfNickAdams Context triple: [A Train Trip, characterTypeOfNickAdams, recurring character]
-
A.
characterTypeOfEdward
Indicates that the specified attribute or classification is the character type assigned to Edward.
-
B.
typeOfCharacter
chosen
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
C.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
-
D.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
E.
characterPersona
Indicates that one entity embodies, represents, or assumes the persona, role, or character identity specified by another entity.
- 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_69f76dc513fc819084a1ff52abbfa5bc |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff7c96e6dc8190b89554480ebcea39 |
completed | May 9, 2026, 6:27 p.m. |
| PD | Predicate disambiguation | batch_69ff7c2381748190ad9a2176e0e478cd |
completed | May 9, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4 p.m.