Triple
T1362179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilsons |
E29119
|
entity |
| Predicate | typicalUsageContext |
P2529
|
FINISHED |
| Object | reference to a family unit |
—
|
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: reference to a family unit | Statement: [Wilsons, typicalUsageContext, reference to a family unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUsageContext Context triple: [Wilsons, typicalUsageContext, reference to a family unit]
-
A.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
typicalUseLocation
Indicates the usual or most common location where an entity is used or operates.
-
D.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
E.
usedPrimarilyIn
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2b4ab3c8190ad692e32eee05976 |
completed | March 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69a4bef945c08190a027472fdd695ea5 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.