Triple
T31173968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ralph Drowne |
E794688
|
entity |
| Predicate | reputationBeforeEvent |
P93104
|
FINISHED |
| Object | mediocre craftsman |
—
|
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: mediocre craftsman | Statement: [Ralph Drowne, reputationBeforeEvent, mediocre craftsman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reputationBeforeEvent Context triple: [Ralph Drowne, reputationBeforeEvent, mediocre craftsman]
-
A.
reputationBeforeScandal
Indicates the reputation or public standing an entity had prior to a specific scandal or damaging event.
-
B.
preFireReputation
Indicates the reputation or standing an entity had before a particular fire-related event or incident occurred.
-
C.
reputationEffect
Indicates how one entity’s actions or characteristics influence the perceived reputation or standing of another entity.
-
D.
laterReputation
Indicates that an entity’s reputation or status at a later time is being referred to in relation to an earlier point or context.
-
E.
haveReputation
chosen
Indicates that an entity is recognized or regarded in a certain way by others, reflecting its perceived character, quality, or status.
- 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_69f224d5b9708190b6ca79ad2fd3a28a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c234d648190a243fb2b107136a9 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:07 p.m.