Triple
T9266926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London 2012 Olympic Torch Relay |
E222723
|
entity |
| Predicate | visitedLocationCount |
P87879
|
FINISHED |
| Object | over 1000 towns, cities and villages |
—
|
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: over 1000 towns, cities and villages | Statement: [London 2012 Olympic Torch Relay, visitedLocationCount, over 1000 towns, cities and villages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visitedLocationCount Context triple: [London 2012 Olympic Torch Relay, visitedLocationCount, over 1000 towns, cities and villages]
-
A.
visitedLocation
Indicates that an entity has gone to or spent time at a particular location.
-
B.
visitedBy
Indicates that a location or entity is the destination or target of a visit performed by another entity.
-
C.
visitedDuring
Indicates that one entity was present at or traveled to another entity within a specified time period or event.
-
D.
visitedFor
Indicates that one entity traveled to or attended another entity (such as a place, person, or event) for a specific purpose or reason.
-
E.
numberOfCountriesVisited
Indicates the total count of distinct countries that an entity has visited.
- F. None of above. chosen
Provenance (4 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_69ca841f2e808190a64f4c31903a1332 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd074bac9481909419988a9e8d9bd5 |
completed | April 1, 2026, 11:53 a.m. |
| PD | Predicate disambiguation | batch_69cc7a537bbc8190baee71f556e52a7b |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:33 p.m.