Triple
T8651472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CAS Registry Number |
E205108
|
entity |
| Predicate | hasPartStructure |
P841
|
FINISHED |
| Object | up to 10 digits divided into three hyphen-separated parts |
—
|
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: up to 10 digits divided into three hyphen-separated parts | Statement: [CAS Registry Number, hasPartStructure, up to 10 digits divided into three hyphen-separated parts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartStructure Context triple: [CAS Registry Number, hasPartStructure, up to 10 digits divided into three hyphen-separated parts]
-
A.
hasTwoPartStructure
Indicates that something is composed of exactly two distinct, structured parts that together form a whole.
-
B.
hasPart
Indicates that one entity is a component, segment, or constituent part of another entity.
-
C.
hasHumanStructure
Indicates that one entity possesses or exhibits a structural form or organization characteristic of humans.
-
D.
hasPartIn
Indicates that an entity participates in or plays a role within a larger event, process, or composite entity.
-
E.
hasStructureType
chosen
Indicates that an entity possesses or is classified by a specific structural type or configuration.
- 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48150e6c8190a7a3b92b4b640858 |
completed | March 31, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69cc45619460819091e83ffdec99c865 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:29 p.m.