Triple
T28904520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Charrington |
E733036
|
entity |
| Predicate | initialDescription |
P53747
|
FINISHED |
| Object | elderly man with mild, benevolent manner |
—
|
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: elderly man with mild, benevolent manner | Statement: [Mr. Charrington, initialDescription, elderly man with mild, benevolent manner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initialDescription Context triple: [Mr. Charrington, initialDescription, elderly man with mild, benevolent manner]
-
A.
firstStageDescription
Indicates that the value provides a textual explanation or summary of the initial or earliest stage in a multi-stage process or sequence.
-
B.
initialOpening
Indicates the first or earliest instance in which something is opened, begun, or made accessible.
-
C.
firstDescriptionContext
chosen
Indicates the primary or initial situational context in which a description of something is given.
-
D.
firstMeetingDescription
Indicates a textual description of what happened or was communicated during the first meeting between the involved entities.
-
E.
initialStatus
Indicates the original or starting state assigned to an entity before any changes or updates occur.
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 28, 2026, 8:05 a.m.