Triple
T8930763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muslim Moors |
E212646
|
entity |
| Predicate | legalStatusInSriLanka |
P46234
|
FINISHED |
| Object | recognized ethnic category in national census |
—
|
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: recognized ethnic category in national census | Statement: [Muslim Moors, legalStatusInSriLanka, recognized ethnic category in national census]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusInSriLanka Context triple: [Muslim Moors, legalStatusInSriLanka, recognized ethnic category in national census]
-
A.
ethnicStatusInSriLanka
chosen
Indicates the ethnic classification or status a person or group holds within the sociopolitical context of Sri Lanka.
-
B.
legalStatusInMyanmar
Indicates the legal status or standing that an entity holds under the laws and regulations of Myanmar.
-
C.
legalStatusInTaiwan
Indicates the legal status or recognition that an entity has within the jurisdiction of Taiwan.
-
D.
legalStatusInChina
Indicates the legal status or standing that an entity holds under the laws and regulations of China.
-
E.
legalStatusInHomeland
Indicates the legal status or classification an entity holds within its country or place of origin.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6676d5d881908ce78cbb5561a68b |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:57 p.m.