Triple
T25766193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tattoo You Tour |
E648890
|
entity |
| Predicate | mainlyTookPlaceIn |
P84795
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [Tattoo You Tour, mainlyTookPlaceIn, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainlyTookPlaceIn Context triple: [Tattoo You Tour, mainlyTookPlaceIn, United States]
-
A.
tookPlaceInAdministrativeEntity
Indicates that an event or occurrence happened within the jurisdiction or boundaries of a specific administrative entity.
-
B.
takesPlaceInRegion
chosen
Indicates that an event or occurrence happens within the boundaries of a specified geographic or administrative region.
-
C.
locationGaveRiseTo
Indicates that a particular location is the origin or source from which something (such as an event, movement, phenomenon, or entity) emerged or developed.
-
D.
tookPlaceFrom
Indicates that an event or occurrence started or was ongoing beginning at a specified time or location.
-
E.
mainlyObservedIn
Indicates that something occurs, appears, or is found predominantly within a particular context, location, group, or condition.
- 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_69e7ab322db0819092d6a2b3d4572e01 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fdf3b14c8190b246bfb191815fd5 |
completed | May 2, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69f4a0fed15881909b789251fe5d8d45 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 22, 2026, 5:10 a.m.