Triple
T38312531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union City |
E1033727
|
entity |
| Predicate | economicScale |
P190788
|
FINISHED |
| Object | local |
—
|
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: local | Statement: [Union City, economicScale, local]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicScale Context triple: [Union City, economicScale, local]
-
A.
economicScope
Indicates the range or extent of economic activities, impacts, or considerations that a given entity, action, or relationship encompasses.
-
B.
economicExtensionOf
Indicates that one entity’s economy is heavily dependent on, controlled by, or functions as an outgrowth of another entity’s economic system.
-
C.
economicSystem
Indicates the type or structure of the economic organization or system under which an entity operates or to which it belongs.
-
D.
businessScale
Indicates the relative size or level of operations of a business, such as its scope, capacity, or market reach.
-
E.
economicAspect
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
- 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_69f76e132c408190969b3d35c04b87ae |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fcd148e6d4819082c118832ecc599b |
completed | May 7, 2026, 5:52 p.m. |
Created at: May 3, 2026, 4:30 p.m.