Triple
T2086269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fannie |
E45356
|
entity |
| Predicate | usagePeak |
P34607
|
FINISHED |
| Object | late 19th century |
—
|
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: late 19th century | Statement: [Fannie, usagePeak, late 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usagePeak Context triple: [Fannie, usagePeak, late 19th century]
-
A.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
hasPeakHourService
Indicates that a service operates or is available during designated peak or high-demand hours.
-
C.
airPowerUsedBy
Indicates that a particular actor employs or deploys air power (such as aircraft or aerial operations) as part of its activities or capabilities.
-
D.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
-
E.
commercialPeak
Indicates the time or period when something (such as a product, artist, or business) achieves its highest level of commercial success or popularity.
- F. None of above. chosen
Provenance (4 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_69a8891869c88190a02643e3bb746f59 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba54ec048190bfe378aef1cc8086 |
completed | March 7, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69abb7b4356881909217c42ccb8bb1ed |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb83e7888819096dc40275c77daff |
completed | March 7, 2026, 5:31 a.m. |
Created at: March 4, 2026, 7:41 p.m.