Triple
T4234089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South-Central Texas |
E94650
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Boerne |
E206386
|
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: Boerne | Statement: [South-Central Texas, containsCity, Boerne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boerne Context triple: [South-Central Texas, containsCity, Boerne]
-
A.
Boerne
chosen
Boerne is a small, historic town in south-central Texas known for its German heritage, charming downtown, and scenic Hill Country surroundings.
-
B.
Ebersole
Ebersole is a surname most notably associated with American actress and singer Christine Ebersole.
-
C.
Boren
Boren is a surname most prominently associated with American politician and former Oklahoma governor and U.S. senator David Boren.
-
D.
Kingsburg
Kingsburg is a small, historically Swedish-themed city in California’s San Joaquin Valley known for its agricultural community and distinctive Scandinavian character.
-
E.
Nyhausen
Nyhausen is a locality in Germany historically noted as the birthplace of the Swedish nobleman and soldier Philip Christoph von Königsmarck.
- 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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e6705548190b695b3789d713b4a |
completed | March 12, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5965316588190ac1a963a5ecfcdaa |
completed | March 14, 2026, 5:09 p.m. |
Created at: March 12, 2026, 11:05 p.m.