Triple
T1777169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas A&M University Health Science Center |
E39206
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Bryan |
E186599
|
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: Bryan | Statement: [Texas A&M University Health Science Center, city, Bryan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bryan Context triple: [Texas A&M University Health Science Center, city, Bryan]
-
A.
Bryan
chosen
Bryan is a masculine given name of Celtic origin that is widely used in English-speaking countries.
-
B.
Brett
Brett is the given name of Brett M. Kavanaugh, an Associate Justice of the United States Supreme Court.
-
C.
Tyler Bight
Tyler Bight is a coastal inlet or bay located along the shores of San Miguel Island in California’s Channel Islands.
-
D.
Brandon
Brandon is a masculine given name of Old English origin meaning "hill covered with broom" or "beacon hill."
-
E.
Brandon
Brandon is a town in Suffolk, England, known for its location on the Breckland railway line and its surrounding Breckland heathland and forestry.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa64b967f08190a73216361b9c2d83 |
completed | March 6, 2026, 5:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5c96694819085f3ccafb141802f |
completed | March 8, 2026, 5:45 p.m. |
Created at: March 4, 2026, 7:31 p.m.