Triple
T14693044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawthorne neighborhood of Cicero |
E345082
|
entity |
| Predicate | hasEraOfGrowth |
P24285
|
FINISHED |
| Object | industrial era of early 1900s |
—
|
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 era of early 1900s | Statement: [Hawthorne neighborhood of Cicero, hasEraOfGrowth, industrial era of early 1900s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEraOfGrowth Context triple: [Hawthorne neighborhood of Cicero, hasEraOfGrowth, industrial era of early 1900s]
-
A.
hadGrowthPeriod
chosen
Indicates that an entity experienced a specific span of time during which it underwent growth or development.
-
B.
hasGrowingSector
Indicates that a particular sector or industry is experiencing growth or expansion over time.
-
C.
historicalEraOfSuccess
Indicates that an entity achieved notable success or prominence during a specified historical era.
-
D.
hasCommercialGrowth
Indicates that an entity experiences or exhibits an increase in commercial activity, revenue, or market presence over time.
-
E.
hasGrowthRate
Indicates the rate at which something increases in size, quantity, or value over a given period of time.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb586e7108190be644db9cf9a4d99 |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de6579fb7881909becc8f5822b39d4 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.