Triple
T9472270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eliza |
E228419
|
entity |
| Predicate | nameUsageFrequency |
P77533
|
FINISHED |
| Object | 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: common | Statement: [Eliza, nameUsageFrequency, common]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameUsageFrequency Context triple: [Eliza, nameUsageFrequency, common]
-
A.
hasNameGenderUsage
Indicates that a particular name is used with a specific gender or set of genders in a given context.
-
B.
frequencyContent
chosen
Indicates that one entity specifies or characterizes the rate or frequency with which the content or occurrence of another entity takes place.
-
C.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
-
D.
rankByFrequencyInPoland
Indicates the relative ordering of entities based on how often they occur or appear in Poland.
-
E.
frequencyInUS
Indicates how often something occurs, appears, or is used within the United States.
- 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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fef6f288190b2d158c829b31de9 |
completed | April 1, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69cca55f01b081908dc0f12eaa45f832 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:54 p.m.