Triple
T567230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division of Polymeric Materials: Science and Engineering |
E13579
|
entity |
| Predicate | topicIncludes |
P1393
|
FINISHED |
| Object | polymer synthesis |
—
|
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: polymer synthesis | Statement: [Division of Polymeric Materials: Science and Engineering, topicIncludes, polymer synthesis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topicIncludes Context triple: [Division of Polymeric Materials: Science and Engineering, topicIncludes, polymer synthesis]
-
A.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
B.
frequentlyDiscussedIn
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
-
C.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
D.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
E.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b01aca48190944408d066519149 |
completed | March 1, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69a494c183b081909304944aa3d0fe8f |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.