Triple
T10977871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Court Theatre (Chicago) |
E259418
|
entity |
| Predicate | cityTheatreScene |
P6534
|
FINISHED |
| Object | part of Chicago theatre community |
—
|
LITERAL 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: part of Chicago theatre community | Statement: [Court Theatre (Chicago), cityTheatreScene, part of Chicago theatre community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityTheatreScene Context triple: [Court Theatre (Chicago), cityTheatreScene, part of Chicago theatre community]
-
A.
theaterExperience
Indicates that an entity has experience or involvement in theater-related activities or performances.
-
B.
relatedTheater
chosen
Indicates a relationship where one entity is associated with, connected to, or relevant in the context of a particular theater or theatrical venue.
-
C.
theaterFocus
Indicates a relationship where an entity’s primary attention, activity, or specialization is centered on theater or theatrical performance.
-
D.
typicalTheatre
Indicates that something is characteristic of or commonly found in a theatre setting.
-
E.
theater
Indicates that an entity is a theater or is functioning in the role of a theater (a venue where performances or films are shown).
- F. None of above.
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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771f6a9448190b3932ee801ae0da9 |
completed | April 9, 2026, 9:31 a.m. |
| PD | Predicate disambiguation | batch_69d72e9055908190b438f039574aaaaf |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.