Triple
T21932537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casanova’s Chinese Restaurant |
E541602
|
entity |
| Predicate | exploresMilieu |
P1857
|
FINISHED |
| Object | London artistic circles |
—
|
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: London artistic circles | Statement: [Casanova’s Chinese Restaurant, exploresMilieu, London artistic circles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exploresMilieu Context triple: [Casanova’s Chinese Restaurant, exploresMilieu, London artistic circles]
-
A.
explores
chosen
Indicates actively investigating, traveling through, or examining something in order to discover or learn more about it.
-
B.
exploresFor
Indicates that one entity actively investigates or searches within or on behalf of another entity, typically to discover or obtain something for that other entity’s benefit.
-
C.
explorationType
Indicates the specific kind or category of exploration activity associated with an entity or event.
-
D.
explorationUse
Indicates the use of something specifically for exploration or investigative activities.
-
E.
explored
Indicates that an entity has traveled through, examined, or investigated another entity or area, typically to discover or learn more about it.
- 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_69e0c47d74488190a15119108794a307 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f123ffde64819084a869d2d569718f |
completed | April 28, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:47 p.m.