Triple
T32581872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miller Theater (Philadelphia) |
E832810
|
entity |
| Predicate | programmingDiversity |
P131133
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Miller Theater (Philadelphia), programmingDiversity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: programmingDiversity Context triple: [Miller Theater (Philadelphia), programmingDiversity, high]
-
A.
programDiversity
chosen
Indicates that there is a diversity of programs, offerings, or activities present within or associated with the referenced entity.
-
B.
programmingBy
Indicates that one entity is created, implemented, or developed through the act of programming performed by another entity.
-
C.
programming
Indicates that an entity writes, develops, or modifies software or code, typically using a programming language to create or control computer programs.
-
D.
providedProgramming
Indicates that one entity supplied or made available programming (such as software, code, or a program) to another entity.
-
E.
programmingIncludes
Indicates that one programming-related entity contains, incorporates, or makes use of another as a part, feature, or component.
- 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_69f349289adc81909f4374a58ec35a39 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f727afd5d88190ad48735cd1b32787 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72737c42c8190a3f781a5e98868ff |
completed | May 3, 2026, 10:45 a.m. |
Created at: May 1, 2026, 1:04 a.m.