Triple
T37792694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMCLs |
E942125
|
entity |
| Predicate | MCLsAre |
P189226
|
FINISHED |
| Object | health-based enforceable standards |
—
|
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: health-based enforceable standards | Statement: [SMCLs, MCLsAre, health-based enforceable standards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MCLsAre Context triple: [SMCLs, MCLsAre, health-based enforceable standards]
-
A.
hasMC
Indicates that an entity has, features, or is associated with a main character (MC).
-
B.
originalMLSClub
Indicates the Major League Soccer club with which an entity (typically a player) was first officially associated or began their MLS career.
-
C.
isMICFor
Indicates that one entity represents the minimum inhibitory concentration (MIC) value determined for another entity, typically a microorganism or drug.
-
D.
hadMLA
Indicates that an entity was represented by, or had as its legislative representative, a particular Member of the Legislative Assembly (MLA).
-
E.
hasLCClassification
Indicates that an entity is assigned a specific Library of Congress Classification code representing its subject or shelving category.
- 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_69f76ee6f1f4819091e2cf9c9e6aee19 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbb9e69b7481909beaf8264d87c5e5 |
completed | May 6, 2026, 10 p.m. |
Created at: May 3, 2026, 4:19 p.m.