Triple
T12163017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dominion Theatre |
E289754
|
entity |
| Predicate | notableLongRunStartYear |
P90029
|
FINISHED |
| Object | 2002 |
—
|
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: 2002 | Statement: [Dominion Theatre, notableLongRunStartYear, 2002]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLongRunStartYear Context triple: [Dominion Theatre, notableLongRunStartYear, 2002]
-
A.
notableEraStart
Indicates the point in time when a notable or historically significant era associated with an entity begins.
-
B.
beganInYear
Indicates that an event, process, or state started in a specific calendar year.
-
C.
firstMajorRunYear
chosen
Indicates the year in which something (such as an event, production, or operation) first began its major or primary run.
-
D.
recordStartYear
Indicates the calendar year in which a particular record, entry, or data instance first began or was created.
-
E.
personalBestMarathonYear
Indicates the year in which an entity achieved their personal best performance in a marathon.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.