Triple
T5015383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Jobs Theater |
E112729
|
entity |
| Predicate | openedForEvents |
P990
|
FINISHED |
| Object | September 2017 |
—
|
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: September 2017 | Statement: [Steve Jobs Theater, openedForEvents, September 2017]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedForEvents Context triple: [Steve Jobs Theater, openedForEvents, September 2017]
-
A.
openedForEvent
Indicates that a venue or location is made accessible and operational specifically for a particular event.
-
B.
openedForUse
chosen
Indicates that something has been made accessible and available for its intended operation or use.
-
C.
openingOccasion
Indicates the event, circumstance, or occasion during which an opening (such as a launch, inauguration, or start) takes place.
-
D.
openedForPublic
Indicates that something has been made accessible or available for use, entry, or participation by the general public.
-
E.
opens
Indicates that one entity causes or allows another entity (such as an object, space, or resource) to become accessible or no longer closed.
- 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd732e0b848190858407920e7aefd0 |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.