Triple
T6874482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerium |
E158638
|
entity |
| Predicate | addressesCondition |
P73866
|
FINISHED |
| Object | dandruff |
—
|
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: dandruff | Statement: [Kerium, addressesCondition, dandruff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressesCondition Context triple: [Kerium, addressesCondition, dandruff]
-
A.
addresses
Indicates that one entity directs speech, communication, or written correspondence specifically toward another entity.
-
B.
addressesBehavior
Indicates that one entity’s actions or policies are directed toward managing, influencing, or responding to the behavior of another entity.
-
C.
addressedThrough
Indicates that an issue, request, or communication is handled, resolved, or processed by means of a specified channel, method, or intermediary.
-
D.
addressesRole
Indicates that one entity directs communication, content, or action specifically toward another entity in its capacity or function as a particular role.
-
E.
appointmentCondition
Indicates the specific terms, requirements, or circumstances that must be met or that apply for an appointment to be scheduled, valid, or carried out.
- 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_69c68832af1481908ce356e133ebaebe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8c8d3888190b1c1f74aa66d6071 |
completed | March 27, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b363dc8190a7225b540ab2bc40 |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c48ba48190b8d3aa7b8d22816b |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:22 p.m.