Triple
T20021708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zduńska Wola |
E494875
|
entity |
| Predicate | hasIndustrialTraditionIn |
P19423
|
FINISHED |
| Object | textile industry |
—
|
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: textile industry | Statement: [Zduńska Wola, hasIndustrialTraditionIn, textile industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustrialTraditionIn Context triple: [Zduńska Wola, hasIndustrialTraditionIn, textile industry]
-
A.
hasIndustrialHeritage
Indicates that an entity possesses or is associated with historically significant industrial sites, structures, or practices.
-
B.
hasIndustrialTown
Indicates that an entity possesses or is associated with a town characterized primarily by industrial activities or facilities.
-
C.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
D.
hasTraditionIn
chosen
Indicates that a particular tradition, custom, or longstanding practice is present, observed, or established within a specified place, group, or context.
-
E.
industrialCategory
Indicates the industry or sector classification to which an entity (such as a business or organization) belongs.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66288fc18819083833b55c5e069a6 |
completed | April 20, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:35 p.m.