Triple
T504804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Inn Kitchen |
E10480
|
entity |
| Predicate | hasCharacterType |
P10724
|
FINISHED |
| Object | innkeeper |
—
|
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: innkeeper | Statement: [The Inn Kitchen, hasCharacterType, innkeeper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacterType Context triple: [The Inn Kitchen, hasCharacterType, innkeeper]
-
A.
hasTypicalCharacterType
chosen
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
-
B.
characterSetType
Indicates the type or category of character set associated with or used by an entity.
-
C.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
D.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
E.
hasChromosomeType
Indicates a relationship where an entity is associated with or characterized by a specific type or category of chromosome.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f149bd1c81908ff58ac504ace2bf |
completed | Feb. 28, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69a2edfce7a08190a408bc019de60d5d |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.