Triple
T191826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rust Belt |
E3736
|
entity |
| Predicate | hasTrend |
P5318
|
FINISHED |
| Object | efforts at economic revitalization |
—
|
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: efforts at economic revitalization | Statement: [Rust Belt, hasTrend, efforts at economic revitalization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrend Context triple: [Rust Belt, hasTrend, efforts at economic revitalization]
-
A.
hasTrail
Indicates that an entity possesses, includes, or is associated with a trail or pathway.
-
B.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
-
C.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
D.
isPopularWith
Indicates that one entity is well-liked, favored, or widely accepted by another entity or group.
-
E.
hasTerm
Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
- F. None of above. chosen
Provenance (4 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a259669ba08190a5be1d2e10e70b27 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a2567567508190b3a41329a15c7156 |
completed | Feb. 28, 2026, 2:44 a.m. |
| PDg | Predicate description generation | batch_69a25710bdfc81909b6697159104cf53 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.