Triple
T26505216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsesta |
E669524
|
entity |
| Predicate | traditionalTreatmentMethod |
P122242
|
FINISHED |
| Object | hydrogen sulfide baths |
—
|
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: hydrogen sulfide baths | Statement: [Matsesta, traditionalTreatmentMethod, hydrogen sulfide baths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalTreatmentMethod Context triple: [Matsesta, traditionalTreatmentMethod, hydrogen sulfide baths]
-
A.
traditionalCareBy
Indicates that one entity receives traditional or culturally rooted care, treatment, or support from another entity.
-
B.
traditionalProductionMethod
Indicates that something is created or carried out using long-established, customary techniques rather than modern or industrial methods.
-
C.
primaryTreatment
Indicates that a specified treatment is the main or first-line intervention used to address a particular condition or problem, as opposed to secondary or adjunctive treatments.
-
D.
treatmentType
chosen
Indicates the specific kind or category of treatment applied or prescribed in relation to an entity or condition.
-
E.
traditionalCatch
Indicates that an entity captures or obtains something using customary or long-established methods rather than modern or unconventional techniques.
- 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_69eeb319ec70819090834c2591cf5f1e |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: April 27, 2026, 1:15 a.m.