Triple
T4354009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troy University |
E98100
|
entity |
| Predicate | hasMainCampus |
P115
|
FINISHED |
| Object | Troy, Alabama |
E100954
|
NE 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: Troy, Alabama | Statement: [Troy University, hasMainCampus, Troy, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troy, Alabama Context triple: [Troy University, hasMainCampus, Troy, Alabama]
-
A.
Troy, Alabama, United States
chosen
Troy, Alabama, United States, is a small city in southeastern Alabama known as the hometown of civil rights leader and longtime U.S. Congressman John Lewis.
-
B.
Trussville, Alabama
Trussville, Alabama is a growing suburban city in Jefferson and St. Clair counties known for its family-friendly neighborhoods, schools, and proximity to Birmingham.
-
C.
Pelham, Alabama
Pelham, Alabama is a suburban city in Shelby County known for its proximity to Birmingham and attractions like Oak Mountain State Park.
-
D.
Moody, Alabama
Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
-
E.
Gadsden, Alabama
Gadsden, Alabama is a small industrial city in northeastern Alabama known historically for its manufacturing plants and labor history.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351c281688190aef717c4ecce8107 |
completed | March 12, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd6f7bfd4c8190adf670a5a11c8182 |
completed | March 20, 2026, 4:02 p.m. |
Created at: March 12, 2026, 11:15 p.m.