Triple
T429368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanukkah |
E9679
|
entity |
| Predicate | candleLightingFrequency |
P13823
|
FINISHED |
| Object | nightly |
—
|
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: nightly | Statement: [Hanukkah, candleLightingFrequency, nightly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: candleLightingFrequency Context triple: [Hanukkah, candleLightingFrequency, nightly]
-
A.
cauldronLighter
Indicates that an entity performs the action of lighting or igniting a cauldron.
-
B.
lightRange
Indicates the distance or area over which a light source effectively emits or illuminates.
-
C.
olympicCauldronLighter
Indicates the person or entity that performs the ceremonial act of lighting the Olympic cauldron at the start of the Olympic Games.
-
D.
lightLevel
Indicates the intensity or amount of light present in a given context or environment.
-
E.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eeedf68c81908473d6c6600961bd |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd7a3608190b8785c7b7205f6c1 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb93584819082f23eff13e17c4f |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.