Triple
T2739573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin University |
E60715
|
entity |
| Predicate | nonResidential |
P41766
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Franklin University, nonResidential, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonResidential Context triple: [Franklin University, nonResidential, true]
-
A.
isResidential
Indicates that something is used or designated primarily for people to live in, rather than for commercial, industrial, or other non-living purposes.
-
B.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
-
C.
nonExclusive
Indicates that the relationship or access is shared among multiple parties and is not limited to a single, exclusive holder.
-
D.
secondaryLandUse
Indicates a secondary or additional way in which a piece of land is used, beyond its primary designated use.
-
E.
property
Indicates that one entity possesses, is characterized by, or has an attribute or quality associated with another entity.
- 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_69ab4b77febc819095603eb012cd141b |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb2da94c8190bc9d23262e3dfc07 |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd82859348190bce3be8f2e9d60ba |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd968b2148190929af432c9d8001f |
completed | March 7, 2026, 7:53 a.m. |
Created at: March 6, 2026, 9:56 p.m.