Triple
T27156607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy Valley (Penn State region) |
E682534
|
entity |
| Predicate | popularNameUsedBy |
P71235
|
FINISHED |
| Object | students |
—
|
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: students | Statement: [Happy Valley (Penn State region), popularNameUsedBy, students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularNameUsedBy Context triple: [Happy Valley (Penn State region), popularNameUsedBy, students]
-
A.
popularName
Indicates that the object is a commonly used or widely recognized name or nickname for the subject.
-
B.
usedAsNamesakeFor
Indicates that one entity serves as the source or inspiration for the name given to another entity.
-
C.
nicknamedFor
Indicates that one entity serves as the source, inspiration, or reason for another entity’s nickname.
-
D.
surnameUsedIn
Indicates that a particular surname is used or borne within a specified context, such as by a person, family, or group.
-
E.
oftenUsedAsNameFor
chosen
Indicates that something frequently serves as a name or designation 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_69eefaceb2a08190b9659b7f730629f5 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 27, 2026, 9:16 a.m.