Triple
T33799329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Bridger |
E866168
|
entity |
| Predicate | hasMannerisms |
P193399
|
FINISHED |
| Object | refined and gentlemanly behavior |
—
|
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: refined and gentlemanly behavior | Statement: [Mr. Bridger, hasMannerisms, refined and gentlemanly behavior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMannerisms Context triple: [Mr. Bridger, hasMannerisms, refined and gentlemanly behavior]
-
A.
hasManner
Indicates the way, style, or method in which an action is performed or a relation is carried out.
-
B.
hasPersonalityDescribedAs
Indicates that an entity possesses a personality characterized or labeled in a particular way.
-
C.
hasDifferentPersonalityIn
Indicates that an entity exhibits a different personality or character traits within a specified context, setting, or situation.
-
D.
hasEtiquette
chosen
Indicates that an entity follows or embodies proper manners, social norms, or courteous behavior in interactions with others.
-
E.
hasSpeakingStyle
Indicates that one entity exhibits or is characterized by a particular manner or style of speaking in relation to 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_69f3498f99f481909cb271f4965a7594 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a013f09b0988190ba3179c7d56c726a |
completed | May 11, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_6a013e600e248190a1a9c363702c8586 |
completed | May 11, 2026, 2:26 a.m. |
Created at: May 1, 2026, 1:46 a.m.