Triple
T351402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Room |
E7449
|
entity |
| Predicate | notableEventHeld |
P2107
|
FINISHED |
| Object | state dinners receptions |
—
|
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: state dinners receptions | Statement: [East Room, notableEventHeld, state dinners receptions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableEventHeld Context triple: [East Room, notableEventHeld, state dinners receptions]
-
A.
notableEventCoverage
Indicates that there is media or documented coverage specifically focused on a notable event related to the subject.
-
B.
notableEventDate
Indicates the date on which a notable or significant event associated with the subject occurred.
-
C.
annualEvent
Indicates that an event occurs once every year on a recurring basis.
-
D.
hasHistoricalEvent
chosen
Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
-
E.
notableTournament
Indicates that an entity is a tournament of particular significance or prominence in relation to another entity.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7df63c8190b7cd1bcfdfd96187 |
completed | Feb. 28, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69a2e955d1f88190bd687c46fa7c5469 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.