Triple
T15217487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moda, Inc. |
E363674
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Moda Health |
E74093
|
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: Moda Health | Statement: [Moda, Inc., hasBrand, Moda Health]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moda Health Context triple: [Moda, Inc., hasBrand, Moda Health]
-
A.
Moda Health
chosen
Moda Health is a U.S.-based health insurance and employee benefits company known for providing medical, dental, and related coverage, particularly in the Pacific Northwest.
-
B.
Moda Health Plan, Inc.
Moda Health Plan, Inc. is a regional health insurance company in the United States that offers medical, dental, and related health coverage to individuals, employers, and government programs.
-
C.
Moda, Inc.
Moda, Inc. is a U.S.-based healthcare company that operates insurance and related health services businesses, including Moda Health.
-
D.
Omada Health
Omada Health is a digital health company that delivers evidence-based, virtual care programs to help people prevent and manage chronic conditions such as diabetes, hypertension, and obesity.
-
E.
Inexmoda
Inexmoda is a Colombian institute that promotes and develops the fashion and textile industry in Latin America through major trade fairs, research, and industry support programs.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076f90c481909989befe031a2cae |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01dc23d081908ad6985bae5741ce |
completed | May 9, 2026, 9:43 a.m. |
Created at: April 10, 2026, 3:11 a.m.