Triple
T19768044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lag LaOmer |
E474809
|
entity |
| Predicate | dayOfOmerCount |
P59693
|
FINISHED |
| Object | 33 |
—
|
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: 33 | Statement: [Lag LaOmer, dayOfOmerCount, 33]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dayOfOmerCount Context triple: [Lag LaOmer, dayOfOmerCount, 33]
-
A.
dayInOmerCount
chosen
Indicates that one entity specifies which numbered day it is within the sequential counting of the Omer period.
-
B.
timeframeRelativeToRoshHashanah
Indicates the temporal relationship of an event or period in reference to Rosh Hashanah (e.g., before, during, or after the holiday).
-
C.
timeframeRelativeToPassover
Indicates the temporal relationship of an event or action to the time of Passover (e.g., before, during, or after Passover).
-
D.
dayRelativeToEaster
Indicates the temporal offset of a given day relative to the date of Easter in a specific year (e.g., days before or after Easter Sunday).
-
E.
timingRelativeToYomKippur
Indicates how the timing of an event is positioned in relation to Yom Kippur (e.g., before, during, or after the holiday).
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65358fc3c8190867fea2a2c4e7594 |
completed | April 20, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.