Triple
T1022795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | heatless Mondays program |
E22075
|
entity |
| Predicate | implementedInYear |
P10338
|
FINISHED |
| Object | 1918 |
—
|
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: 1918 | Statement: [heatless Mondays program, implementedInYear, 1918]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: implementedInYear Context triple: [heatless Mondays program, implementedInYear, 1918]
-
A.
introducedInYear
Indicates the year in which something was first introduced, launched, or made available.
-
B.
developedAt
Indicates the place or location where something was created, built, or developed.
-
C.
implementedOn
Indicates that something (such as a feature, standard, or specification) is realized, executed, or put into effect within or on a particular platform, system, or environment.
-
D.
beganInYear
chosen
Indicates that an event, process, or state started in a specific calendar year.
-
E.
cameIntoForceInYear
Indicates that a law, agreement, or formal measure became legally effective or operational in a specified calendar year.
- 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.