Triple
T475760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American College of Surgeons |
E9056
|
entity |
| Predicate | hasMembersIn |
P7638
|
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: [American College of Surgeons, hasMembersIn, multiple countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMembersIn Context triple: [American College of Surgeons, hasMembersIn, multiple countries]
-
A.
hasMembers
chosen
Indicates that a group, organization, or collection includes certain entities as its members.
-
B.
hasListOfMembers
Indicates that an entity is associated with a collection containing its members or constituents.
-
C.
hasTeamMember
Indicates that an entity includes another entity as a member of its team.
-
D.
hasAssociateMember
Indicates that an entity has another entity connected to it in a non-full, typically limited or secondary, membership capacity.
-
E.
hadMember
Indicates that an entity was formerly a member or part of another entity or group.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f03b5e5081908ee3dba9d19a6871 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edeed31881908cf43beed410572d |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.