Triple
T25001195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1986 Goodwill Games |
E625722
|
entity |
| Predicate | organizedDuringLeadershipOf |
P160086
|
FINISHED |
| Object | Mikhail Gorbachev |
—
|
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: Mikhail Gorbachev | Statement: [1986 Goodwill Games, organizedDuringLeadershipOf, Mikhail Gorbachev]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: organizedDuringLeadershipOf Context triple: [1986 Goodwill Games, organizedDuringLeadershipOf, Mikhail Gorbachev]
-
A.
hadLeadershipFrom
Indicates that one entity received leadership, guidance, or direction from another entity.
-
B.
constitutesLeadershipOf
Indicates that an entity forms or makes up the leadership of another entity, such as an organization, group, or body.
-
C.
builtDuringGovernorshipOf
Indicates that the construction of one entity occurred during the period when another entity held a governing office.
-
D.
hasLeadershipExperienceIn
Indicates that an entity possesses prior leadership experience specifically within a given domain, context, or organization.
-
E.
leaderDuring
Indicates that one entity serves as the leader of another entity during a specified time period.
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f6018f91248190985323d1a678e539 |
completed | May 2, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f5ffc6268c8190b63f6360ebadab73 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 18, 2026, 6:04 a.m.