Triple
T4736249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Nations Statistical Commission |
E105132
|
entity |
| Predicate | convenesInMonth |
P7705
|
FINISHED |
| Object | March |
—
|
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: March | Statement: [United Nations Statistical Commission, convenesInMonth, March]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: convenesInMonth Context triple: [United Nations Statistical Commission, convenesInMonth, March]
-
A.
convenesOn
Indicates that an event, group, or body holds a meeting or session at a specific time or date.
-
B.
convenesIn
Indicates that an entity brings together or assembles a group, meeting, or event at a specific place or venue.
-
C.
convenesDuring
Indicates that one entity formally gathers or brings together another entity or group during a specified time period or event.
-
D.
convenesAs
Indicates that an entity brings together or assembles a group, body, or session in a particular role or capacity.
-
E.
typicalMeetingMonth
chosen
Indicates the month in which an entity most commonly or usually holds its meetings.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64831c58819098758ac1f7839b3a |
completed | March 20, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69bd6221c3b881908604f35f8de6f16b |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:19 p.m.