Triple
T2980904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aleph |
E80506
|
entity |
| Predicate | relatedLetter |
P44424
|
FINISHED |
| Object | Arabic Alif |
—
|
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: Arabic Alif | Statement: [Aleph, relatedLetter, Arabic Alif]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedLetter Context triple: [Aleph, relatedLetter, Arabic Alif]
-
A.
relatedForm
Indicates that one entity is an alternative or variant form of another, such as a different spelling, inflection, or closely related lexical form.
-
B.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
C.
relatedCase
Indicates that one legal case is connected or associated with another case, such as through shared facts, parties, issues, or procedural history.
-
D.
letter3
Indicates that one entity is the third letter (or character) of another entity, typically a string or word.
-
E.
correspondedWith
Indicates that two entities engaged in mutual communication, typically by exchanging messages or letters over a period of time.
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad999e91788190a2d430dd0600a660 |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad9611fc348190a5d17d237f653f60 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:58 p.m.