Triple
T153563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UN Climate Action Summit 2019 |
E3482
|
entity |
| Predicate | hasParticipantType |
P2434
|
FINISHED |
| Object | heads of state and government |
—
|
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: heads of state and government | Statement: [UN Climate Action Summit 2019, hasParticipantType, heads of state and government]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticipantType Context triple: [UN Climate Action Summit 2019, hasParticipantType, heads of state and government]
-
A.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
B.
hasParticipants
chosen
Indicates that an event, activity, or situation involves one or more entities as participants in it.
-
C.
hasParticleType
Indicates that an entity is associated with, composed of, or characterized by a specific type or category of particle.
-
D.
hasVisitorType
Indicates the type or category of visitor associated with an entity (e.g., guest, customer, tourist, patient).
-
E.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258e0b11c8190b7b5cf3c354c47ce |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2565c727c8190bca9ba6ca52f216a |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.