Triple
T8186912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Fleming |
E191207
|
entity |
| Predicate | nameFrequency |
P42208
|
FINISHED |
| Object | relatively common |
—
|
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: relatively common | Statement: [James Fleming, nameFrequency, relatively common]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameFrequency Context triple: [James Fleming, nameFrequency, relatively common]
-
A.
namePopularityType
chosen
Indicates the category or type of popularity associated with a given name (e.g., how or in what way the name is considered popular).
-
B.
namesAs
Indicates that one entity assigns or uses a particular name or label to refer to another entity.
-
C.
numberOfNames
Indicates the count of distinct names associated with a given entity.
-
D.
namesDay
Indicates that one entity is the name assigned to a particular day (such as a weekday or holiday) associated with another entity.
-
E.
nameLiterallyMeans
Indicates that the literal meaning or direct translation of one entity’s name is given by the other 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_69ca82c5b6948190a583c096fb0a6c71 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4d9e01208190842170abf62d9afb |
completed | March 31, 2026, 4:29 a.m. |
| PD | Predicate disambiguation | batch_69cb36a7952481908f34e3e82f375a84 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:41 p.m.