Triple
T21619935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Historical Civil Engineering Landmark |
E533547
|
entity |
| Predicate | frequencyOfDesignation |
P53048
|
FINISHED |
| Object | occasional |
—
|
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: occasional | Statement: [California Historical Civil Engineering Landmark, frequencyOfDesignation, occasional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyOfDesignation Context triple: [California Historical Civil Engineering Landmark, frequencyOfDesignation, occasional]
-
A.
numberOfDesignations
Indicates the count of distinct designations or titles associated with a given entity.
-
B.
frequencyClass
chosen
Indicates how often an event, action, or relation occurs, typically by assigning it to a predefined frequency category or class.
-
C.
symbolForFrequency
Indicates that one entity serves as the symbolic representation or notation used to denote the frequency of another entity or phenomenon.
-
D.
divisionFrequency
Indicates how often a division event occurs within a given context or time frame.
-
E.
typicalDesignation
Indicates that one entity is the usual or commonly used designation (name, label, or title) for 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef3baeeae48190b78583b3bec8ee33 |
completed | April 27, 2026, 10:34 a.m. |
| PD | Predicate disambiguation | batch_69e69665fe8c8190af7e38785db188b2 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:34 p.m.