Triple
T35707510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syriac Pe |
E1031757
|
entity |
| Predicate | correspondsToArabicLetter |
P125165
|
FINISHED |
| Object | Arabic Faʼ |
—
|
NE NERFINISHED |
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 Faʼ | Statement: [Syriac Pe, correspondsToArabicLetter, Arabic Faʼ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToArabicLetter Context triple: [Syriac Pe, correspondsToArabicLetter, Arabic Faʼ]
-
A.
correspondsToInArabic
chosen
Indicates that one entity is the equivalent or matching counterpart of another entity specifically in the Arabic language.
-
B.
correspondsToLatinLetter
Indicates that one entity is the counterpart or representation of another entity as a specific letter in the Latin alphabet.
-
C.
correspondsToEnglishLetter
Indicates that one entity is the English alphabet letter that matches, represents, or is equivalent to the other entity.
-
D.
correspondsToPhoenicianLetter
Indicates a relationship where one written symbol or character is associated with, or derived from, a specific letter of the Phoenician alphabet.
-
E.
correspondsToChineseCharacter
Indicates that one entity is the equivalent or representation of a specific Chinese written character.
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b2f3a104819098ddd8909eaf596c |
completed | May 3, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:05 p.m.