Triple
T144560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Big Shoulders |
E2925
|
entity |
| Predicate | evokes |
P4750
|
FINISHED |
| Object | Chicago industrial history |
—
|
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: Chicago industrial history | Statement: [City of Big Shoulders, evokes, Chicago industrial history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: evokes Context triple: [City of Big Shoulders, evokes, Chicago industrial history]
-
A.
designedToEvoke
Indicates that something was intentionally created or arranged in order to elicit a particular reaction, feeling, or response from an audience or observer.
-
B.
eve
Indicates a relationship where one entity is the evening or night-time counterpart, phase, or occurrence associated with another entity.
-
C.
expresses
chosen
Indicates that one entity conveys, communicates, or articulates a thought, feeling, or idea through another medium or form.
-
D.
reflects
Indicates that one entity (often a surface, medium, or representation) throws back, mirrors, or otherwise shows an image, property, or state of another entity.
-
E.
encourages
Indicates actively motivating, supporting, or giving confidence to another entity to pursue an action, behavior, or state.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257e935bc8190a03e54a10e9ba6f7 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a25656a4fc81908a87678ac3d28f93 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.