Triple
T320616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippine Independent Church |
E6405
|
entity |
| Predicate | hasApproximateMembers |
P9078
|
FINISHED |
| Object | millions of members |
—
|
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: millions of members | Statement: [Philippine Independent Church, hasApproximateMembers, millions of members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateMembers Context triple: [Philippine Independent Church, hasApproximateMembers, millions of members]
-
A.
hasCurrentNumberOfMembers
chosen
Indicates the current count of members associated with a given entity.
-
B.
hasMembers
Indicates that a group, organization, or collection includes certain entities as its members.
-
C.
numberOfKnownMembers
Indicates the count of members within a group or set whose identities are known or have been explicitly determined.
-
D.
hasApproximateValue
Indicates that one entity’s value is close to, but not exactly equal to, the value of another entity within an acceptable margin of error.
-
E.
hasMemberCountType
Indicates the type or classification used to describe how the number of members in a group or collection is represented.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea8047c08190872c875e00f6e7dd |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.