Triple
T9698920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lela |
E234723
|
entity |
| Predicate | meaningInArabicRoot |
P30734
|
FINISHED |
| Object | night |
—
|
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: night | Statement: [Lela, meaningInArabicRoot, night]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningInArabicRoot Context triple: [Lela, meaningInArabicRoot, night]
-
A.
etymologicalRootMeaning
Indicates that one term’s meaning originates from or is derived from the historical or original meaning of another term.
-
B.
nameMeaningInArabic
chosen
Indicates that the predicate specifies the meaning or interpretation of a name when expressed in the Arabic language.
-
C.
hebrewMeaning
Indicates that one entity specifies or provides the meaning or translation of another entity in the Hebrew language.
-
D.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
-
E.
hasMeaningInPersian
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning when interpreted in the Persian language.
- 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d3d425c8190b652d84186b5ce9f |
completed | April 1, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69cd03b641408190942464eaf174c6b5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:18 p.m.