Triple
T11628451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mata Sundari |
E276333
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Mata |
E100841
|
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: Mata | Statement: [Mata Sundari, title, Mata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mata Context triple: [Mata Sundari, title, Mata]
-
A.
Mata
chosen
Mata is a title used in certain South Asian cultural and religious contexts, often signifying a revered mother figure or goddess.
-
B.
Mazani
Mazani is an alternative name for the Mazanderani language, an Iranian language spoken primarily along the southern coast of the Caspian Sea in northern Iran.
-
C.
Matta
Matta is a surname most prominently associated with Thad Matta, a successful American college basketball coach known for his tenures at Xavier and Ohio State.
-
D.
Matta
Matta is a town located in Pakistan’s Swat District, known for its agricultural surroundings and scenic mountainous landscape.
-
E.
Mambae
Mambae is an Austronesian language spoken primarily in the central and eastern regions of Timor-Leste.
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a1259cd08190a75eeacb5e39b858 |
completed | April 10, 2026, 7:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef135cde4881908d1cf9f752592d60 |
completed | April 27, 2026, 7:42 a.m. |
Created at: April 8, 2026, 9:39 p.m.