Triple
T3801247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guatemala Highlands |
E91692
|
entity |
| Predicate | hasEthnicGroup |
P1898
|
FINISHED |
| Object | Mam Maya |
E86612
|
NE 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: Mam Maya | Statement: [Guatemala Highlands, hasEthnicGroup, Mam Maya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mam Maya Context triple: [Guatemala Highlands, hasEthnicGroup, Mam Maya]
-
A.
Majha
Majha is a culturally significant region of Punjab in northern India, traditionally known as the heartland of Sikh culture and history.
-
B.
Mamayi
Mamayi was a powerful 14th-century military and political leader of the Golden Horde who played a central role in its internal power struggles and conflicts with emerging Russian principalities.
-
C.
Mam
chosen
Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
-
D.
Anandamoyi
Anandamoyi is a central character in Rabindranath Tagore’s novel "Gora," known for her deep spirituality, maternal compassion, and pivotal influence on the protagonist’s moral and religious awakening.
-
E.
Ménaka
Ménaka is a town in eastern Mali that serves as an important administrative and trading center in the Sahel region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee7b82c0c81909519c3988b108d8b |
completed | March 9, 2026, 3:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f066e30481909e5baa630f3539e4 |
completed | March 14, 2026, 5:21 a.m. |
Created at: March 9, 2026, 3:15 p.m.