Triple
T10486433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garo people |
E247309
|
entity |
| Predicate | marriageResidencePattern |
P71943
|
FINISHED |
| Object | matrilocal residence |
—
|
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: matrilocal residence | Statement: [Garo people, marriageResidencePattern, matrilocal residence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageResidencePattern Context triple: [Garo people, marriageResidencePattern, matrilocal residence]
-
A.
marriagePattern
Indicates the typical form or structure of a marriage relationship, such as how partners are selected, organized, or related within a social or cultural system.
-
B.
afterMarriageResidence
chosen
Indicates the place or arrangement where individuals live following their marriage.
-
C.
residencyPattern
Indicates the typical way an entity resides or occupies a place over time, such as its usual location, duration, or frequency of stay.
-
D.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
E.
residenceDuringMarriage
Indicates the place where spouses lived or maintained their home during the period of their marriage.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5096988ec81908d7518b09256c145 |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8a30848190b33cf43f005a028e |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:23 p.m.