Triple
T17197851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zilker Hillside Theater |
E417398
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Austin |
—
|
NE NERFINISHED |
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 | Statement: [Zilker Hillside Theater, city, Austin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Austin Context triple: [Zilker Hillside Theater, city, Austin]
-
A.
Austin
chosen
Austin is a major city in central Texas known for its vibrant live music scene, tech industry, and cultural diversity.
-
B.
Austin
Austin is a common English surname of Anglo-Saxon origin, often associated with notable figures in philosophy, politics, and the arts.
-
C.
Austin
Austin is one of Chicago’s largest and most populous West Side community areas, known for its historic residential architecture and significant demographic and economic changes over time.
-
D.
Austin
Austin is a historic British automobile marque best known for its mass-market cars produced throughout much of the 20th century.
-
E.
Austin
Austin is a common English given name used for people of all genders, derived from the Latin name Augustine.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dab718c8190b6f5b08189cf2eb2 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 5:38 a.m.