Triple
T1381465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mustangs |
E29345
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | University Park, Texas |
E45109
|
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: University Park, Texas | Statement: [Mustangs, city, University Park, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: University Park, Texas Context triple: [Mustangs, city, University Park, Texas]
-
A.
University Park, Texas
chosen
University Park, Texas is an affluent suburban city in the Dallas–Fort Worth area best known as the home of Southern Methodist University.
-
B.
College Station, Texas
College Station, Texas is a central Texas city best known as the home of Texas A&M University and its large student-centered community.
-
C.
Cedar Park
Cedar Park is a residential neighborhood in West Philadelphia known for its historic Victorian homes, diverse community, and proximity to the University of Pennsylvania.
-
D.
Duncanville
Duncanville is a suburban city in the Dallas–Fort Worth metropolitan area of North Texas.
-
E.
Princeton, Texas
Princeton, Texas is a small but rapidly growing city in the Dallas–Fort Worth metropolitan area known for its suburban character and proximity to Lake Lavon.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c31b176c8190a896183140c5c8be |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acde1c7e5c8190a6b999f2d5dce088 |
completed | March 8, 2026, 2:25 a.m. |
Created at: March 1, 2026, 7:59 p.m.