Triple
T733981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auschwitz III-Monowitz |
E14890
|
entity |
| Predicate | linkedToIndustry |
P13800
|
FINISHED |
| Object | synthetic rubber production |
—
|
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: synthetic rubber production | Statement: [Auschwitz III-Monowitz, linkedToIndustry, synthetic rubber production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToIndustry Context triple: [Auschwitz III-Monowitz, linkedToIndustry, synthetic rubber production]
-
A.
hasPrincipalIndustry
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
B.
industryConsortium
Indicates a collaborative association where multiple organizations formally join together within an industry to pursue shared goals, standards, or initiatives.
-
C.
positionInIndustry
Indicates the role, rank, or standing that an entity holds within a particular industry or sector.
-
D.
notableIndustry
chosen
Indicates that an entity is significantly recognized or prominent within a specified industry or sector.
-
E.
roleInIndustry
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fafee081909bf356854c09aaff |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.