Triple
T3314988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mont-Blanc Marathon |
E69659
|
entity |
| Predicate | attractsCompetitorsFrom |
P47227
|
FINISHED |
| Object | multiple countries |
—
|
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: multiple countries | Statement: [Mont-Blanc Marathon, attractsCompetitorsFrom, multiple countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attractsCompetitorsFrom Context triple: [Mont-Blanc Marathon, attractsCompetitorsFrom, multiple countries]
-
A.
attractsParticipantsFrom
Indicates that an event, activity, or organization draws or recruits participants originating from a specified place, group, or source.
-
B.
attracts
Indicates that one entity exerts a force or influence that draws another entity toward it.
-
C.
attractsTeamsFrom
Indicates that an entity draws or pulls in teams from another specified entity or location.
-
D.
competesWith
Indicates that two entities are in rivalry or opposition, each striving to outperform or gain advantage over the other in the same domain or objective.
-
E.
successorInMarket
Indicates that one entity has taken over or followed another in serving the same market or customer base.
- 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_69ad85a0bb048190a5458d2738012d61 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb10f97b48190afb9c3864faf8cb2 |
completed | March 8, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69ada4282730819092aa39c5f9269df0 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada52716ec81908e89688a81039394 |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:11 p.m.