Triple
T1022806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | heatless Mondays program |
E22075
|
entity |
| Predicate | hasTargetSector |
P2193
|
FINISHED |
| Object | industrial sector |
—
|
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 sector | Statement: [heatless Mondays program, hasTargetSector, industrial sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetSector Context triple: [heatless Mondays program, hasTargetSector, industrial sector]
-
A.
isSectorSpecific
Indicates that something is tailored or restricted to a particular industry or sector rather than being generally applicable.
-
B.
sectorServed
chosen
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
C.
hasTarget
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
D.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
E.
hasPrincipalIndustry
Indicates that an entity’s main or primary industry of operation is the specified industry.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7e0f8908190bfe0a4cd8b31dfed |
completed | March 1, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69a4b72619cc8190932fdfa0c74dc055 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.