Triple
T3399618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dniprodzerzhynsk Metallurgical Technicum |
E71616
|
entity |
| Predicate | industrySpecialization |
P24922
|
FINISHED |
| Object | metallurgy |
—
|
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: metallurgy | Statement: [Dniprodzerzhynsk Metallurgical Technicum, industrySpecialization, metallurgy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industrySpecialization Context triple: [Dniprodzerzhynsk Metallurgical Technicum, industrySpecialization, metallurgy]
-
A.
marketSpecialization
Indicates a relationship where an entity focuses its activities, products, or services on serving a specific segment or niche of a broader market.
-
B.
industryContext
chosen
Indicates the industry or sector within which an entity, activity, or relationship is situated or most relevant.
-
C.
industryCenter
Indicates that a location functions as a primary hub or focal point for industrial activity or production.
-
D.
industryPerception
Indicates how an industry is viewed or regarded, typically in terms of reputation, trust, or overall public and stakeholder opinion.
-
E.
industryConsortium
Indicates a collaborative association where multiple organizations formally join together within an industry to pursue shared goals, standards, or initiatives.
- 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_69ad85aac4808190a092c9cc8911f584 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb8c6b2b08190a307e33c74cf21ad |
completed | March 8, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69adadfa73ac8190a163f93e88d217f8 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.