Triple
T29153208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catholic Church in Lebanon |
E738966
|
entity |
| Predicate | majorPart |
P11019
|
FINISHED |
| Object | Maronite Church |
—
|
NE NERFINISHED |
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: Maronite Church | Statement: [Catholic Church in Lebanon, majorPart, Maronite Church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorPart Context triple: [Catholic Church in Lebanon, majorPart, Maronite Church]
-
A.
major
Indicates that one entity is the primary field of academic specialization or main area of study for another entity.
-
B.
mainPartOf
Indicates that one entity is the primary or most significant component of another entity.
-
C.
majorSect
chosen
Indicates that one religious sect is the primary, dominant, or most influential branch within a broader religious tradition or context.
-
D.
majorSegmentOf
Indicates that one entity constitutes a principal or most significant part of another larger whole.
-
E.
majorFor
Indicates that an academic program, field of study, or specialization is the primary major associated with a particular student or degree.
- 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_69f07cb46f148190874eb8576a447567 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: April 28, 2026, 11:43 a.m.