Triple
T16513701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lu’an Guapian tea |
E401125
|
entity |
| Predicate | typicalInfusionCount |
P123836
|
FINISHED |
| Object | multiple infusions |
—
|
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: multiple infusions | Statement: [Lu’an Guapian tea, typicalInfusionCount, multiple infusions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalInfusionCount Context triple: [Lu’an Guapian tea, typicalInfusionCount, multiple infusions]
-
A.
bloodUsedFor
Indicates that blood is utilized or applied for a particular purpose, function, or process.
-
B.
hasNumberOfDrops
Indicates the quantity or count of drops associated with an entity or event.
-
C.
hasDosingRegimen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
D.
numberOfPumps
Indicates the quantity of pumps associated with or required by an entity or system.
-
E.
hasMaintenanceDose
Indicates that an entity is associated with a specific ongoing dose used to maintain a desired therapeutic effect after initial treatment.
- F. None of above. chosen
Provenance (4 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e78d4848190a55de9902115b1b2 |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:14 a.m.