Triple
T4688056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Nations Conference on Environment and Development |
E103967
|
entity |
| Predicate | numberOfNGORepresentatives |
P36420
|
FINISHED |
| Object | 10000 |
—
|
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: 10000 | Statement: [United Nations Conference on Environment and Development, numberOfNGORepresentatives, 10000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNGORepresentatives Context triple: [United Nations Conference on Environment and Development, numberOfNGORepresentatives, 10000]
-
A.
numberOfNGOsRepresented
chosen
Indicates the count of distinct non-governmental organizations that are represented in a given context or entity.
-
B.
numberOfResidentOrganizations
Indicates the total count of organizations that are based in or operate from a particular place or entity.
-
C.
numberOfMemberOrganizations
Indicates the total count of organizations that are members of a given group, association, or umbrella entity.
-
D.
numberOfCommitteeMembers
Indicates the total count of individuals who are members of a given committee.
-
E.
numberOfAppointedMembers
Indicates the specific count of members who have been formally appointed to a group, body, or position.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd66059bfc8190885d26d05dd38df1 |
completed | March 20, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69bd6219da948190bbbb50f08573ab4d |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.