Triple
T1180988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beaver |
E25135
|
entity |
| Predicate | worldPremiereLocation |
P128
|
FINISHED |
| Object | Austin, Texas |
E15420
|
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: Austin, Texas | Statement: [The Beaver, worldPremiereLocation, Austin, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Austin, Texas Context triple: [The Beaver, worldPremiereLocation, Austin, Texas]
-
A.
Dallas, Texas
Dallas, Texas is a major metropolitan city in northern Texas known for its role as a commercial and cultural hub, particularly in finance, technology, and telecommunications.
-
B.
Austin
chosen
Austin is a major city in central Texas known for its vibrant live music scene, tech industry, and cultural diversity.
-
C.
Austin
Austin is a small historic mining town in central Nevada known for its 19th-century silver boom and remote, high-desert setting along U.S. Route 50.
-
D.
Frisco, Texas
Frisco, Texas is a rapidly growing suburban city in the Dallas–Fort Worth metropolitan area known for its sports venues, retail centers, and family-friendly communities.
-
E.
San Antonio
San Antonio is a major Chilean port city known for its significant role in the country’s maritime trade and fishing industries.
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd32c5f48190b4e2d39fa052cbb7 |
completed | March 1, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4dadd801481909551f6ed73e02fc2 |
completed | March 14, 2026, 3:49 a.m. |
Created at: March 1, 2026, 7:45 p.m.