Triple
T3578237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baylor Bears |
E75737
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Waco |
E97168
|
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: Waco | Statement: [Baylor Bears, city, Waco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waco Context triple: [Baylor Bears, city, Waco]
-
A.
Waco, Texas
chosen
Waco, Texas is a central Texas city known for being home to Baylor University and its prominent collegiate athletic programs.
-
B.
Wichita Falls, Texas
Wichita Falls, Texas is a mid-sized city in northern Texas known for its oil and gas history, military presence at Sheppard Air Force Base, and role as a regional economic and cultural center.
-
C.
Kerrville
Kerrville is a small city in central Texas known for its scenic Guadalupe River setting, Hill Country landscapes, and vibrant arts and music festivals.
-
D.
Lubbock
Lubbock is a major city in northwest Texas known for its role as an agricultural, educational, and economic hub of the region.
-
E.
Corsicana
Corsicana is a small city in north-central Texas known for its oil boom history and as a regional commercial and transportation hub between Dallas and Houston.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0defe14819095a337a840e33300 |
completed | March 8, 2026, 6:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5336104a081908c5f07e8b4d22c58 |
completed | March 14, 2026, 10:07 a.m. |
Created at: March 8, 2026, 3:21 p.m.