Triple
T818633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stalingrad |
E17702
|
entity |
| Predicate | industrialRole |
P8439
|
FINISHED |
| Object | industrial center |
—
|
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: industrial center | Statement: [Stalingrad, industrialRole, industrial center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industrialRole Context triple: [Stalingrad, industrialRole, industrial center]
-
A.
roleInIndustry
chosen
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
-
B.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
C.
positionInIndustry
Indicates the role, rank, or standing that an entity holds within a particular industry or sector.
-
D.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
E.
urbanRole
Indicates the function, status, or role that an entity holds within an urban or city context.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab976094819086d676404d745750 |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa76a7808190ac7fd9ba1a4cebcb |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.